Prof. Leslie M. Collins Profile

Prof. Leslie M. Collins

Professor

SPIE Involvement:

Author | Instructor

Publications (126)

Proceedings Article | 24 April 2020 Presentation + Paper

How robust are deep object detectors to variability in ground truth bounding boxes? Experiments for target recognition in infrared imagery

Evan Stump, Francisco Reveriano, Leslie Collins, Jordan Malof

Proceedings Volume 11394, 1139418 (2020) https://doi.org/10.1117/12.2565897

KEYWORDS: Data modeling, Infrared imaging, Target detection, Visualization, Performance modeling, Sensors, Infrared radiation, Video, Target recognition, Mathematical modeling

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Proceedings Article | 10 May 2019 Presentation + Paper

How transferable are downward-looking and handheld ground penetrating radar data? Experiments in the context of buried threat detection

Evan Stump, Daniel Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 11012, 110120G (2019) https://doi.org/10.1117/12.2519969

KEYWORDS: Algorithm development, General packet radio service, Detection and tracking algorithms, Sensors, Ground penetrating radar, Antennas, Feature extraction, Data modeling, Radar, Systems modeling

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Proceedings Article | 10 May 2019 Presentation + Paper

Reliable training of convolutional neural networks for GPR-based buried threat detection using the Adam optimizer and batch normalization

Steven Jacobson, Daniël Reichman, Joel Bjornstad, Leslie Collins, Jordan Malof

Proceedings Volume 11012, 1101206 (2019) https://doi.org/10.1117/12.2519798

KEYWORDS: General packet radio service, Convolutional neural networks, Detection and tracking algorithms, Neurons, Control systems, Performance modeling, Data processing, Algorithm development, Data modeling, Network architectures

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Proceedings Article | 10 May 2019 Presentation + Paper

An exploration of gradient-based features for buried threat detection using a handheld ground penetrating radar

Evan Stump, Daniel Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 11012, 110120F (2019) https://doi.org/10.1117/12.2519949

KEYWORDS: Algorithm development, General packet radio service, Sensors, Detection and tracking algorithms, Ground penetrating radar, Feature extraction, Radar, Antennas, Image filtering, Reflection

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Proceedings Article | 30 April 2018 Paper

How much shape information is enough, or too much? Designing imaging descriptors for threat detection in ground penetrating radar data

Daniël Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 10628, 106280E (2018) https://doi.org/10.1117/12.2305880

KEYWORDS: Visualization, General packet radio service, Algorithm development, Feature extraction, Computer programming, Ground penetrating radar, Detection and tracking algorithms, Radar imaging, Sensors, Data processing

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Proceedings Article | 30 April 2018 Presentation + Paper

How do we choose the best model? The impact of cross-validation design on model evaluation for buried threat detection in ground penetrating radar

Jordan Malof, Daniël Reichman, Leslie Collins

Proceedings Volume 10628, 106280C (2018) https://doi.org/10.1117/12.2305793

KEYWORDS: Detection and tracking algorithms, Data modeling, Ground penetrating radar, Algorithm development, Data processing, Feature extraction, Visual process modeling, Unexploded object detection, Threat warning systems

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Proceedings Article | 30 April 2018 Paper

If training data appears to be mislabeled, should we relabel it? Improving supervised learning algorithms for threat detection in ground penetrating radar data

Daniël Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 10628, 106280F (2018) https://doi.org/10.1117/12.2305881

KEYWORDS: General packet radio service, Machine learning, Data analysis, Algorithm development, Detection and tracking algorithms, Data modeling, Ground penetrating radar, Visualization, Antennas, Feature extraction

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Proceedings Article | 30 April 2018 Presentation + Paper

Improving the histogram of oriented gradient feature for threat detection in ground penetrating radar by implementing it as a trainable convolutional neural network

Jordan Malof, John Bralich, Daniël Reichman, Leslie Collins

Proceedings Volume 10628, 106280D (2018) https://doi.org/10.1117/12.2305797

KEYWORDS: General packet radio service, Feature extraction, Neural networks, Convolutional neural networks, Algorithm development, Ground penetrating radar, Detection and tracking algorithms, Data processing, Data modeling, Object recognition

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Proceedings Article | 3 May 2017 Presentation + Paper

Discriminative dictionary learning to learn effective features for detecting buried threats in ground penetrating radar data

Jordan Malof, Daniël Reichman, Leslie Collins

Proceedings Volume 10182, 101820W (2017) https://doi.org/10.1117/12.2263111

KEYWORDS: Chemical species, Visualization, Data modeling, Reconstruction algorithms, Detection and tracking algorithms, Ground penetrating radar, Algorithm development, Machine learning, Remote sensing, Target detection, Feature extraction, Target recognition

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Proceedings Article | 3 May 2017 Presentation + Paper

Sensor fusion for buried explosive threat detection for handheld data

Mary Knox, Colin Rundel, Leslie Collins

Proceedings Volume 10182, 101820D (2017) https://doi.org/10.1117/12.2263013

KEYWORDS: Sensors, General packet radio service, Electromagnetic coupling, Land mines, Sensor fusion, Explosives, Explosives detection, Ground penetrating radar, Electromagnetism, Metals, Detection and tracking algorithms

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Proceedings Article | 3 May 2017 Presentation + Paper

An improved frequency domain feature with partial least-squares dimensionality reduction for classifying buried threats in forward-looking ground-penetrating radar data

Joseph Camilo, Miles Crosskey, Kenneth Morton, Leslie Collins, Jordan Malof

Proceedings Volume 10182, 101821D (2017) https://doi.org/10.1117/12.2263034

KEYWORDS: Principal component analysis, Feature extraction, Image processing, Antennas, Fourier transforms, Ground penetrating radar, Algorithm development, Machine learning, Detection and tracking algorithms, Feature selection, Radar, Remote sensing, Sensors, Image filtering

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Proceedings Article | 3 May 2017 Presentation + Paper

Improvements to the Histogram of Oriented Gradient (HOG) prescreener for buried threat detection in ground penetrating radar data

Daniël Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 10182, 101820U (2017) https://doi.org/10.1117/12.2263107

KEYWORDS: Ground penetrating radar, Radar, Target detection, Explosives, Remote sensing, Detection and tracking algorithms, Machine vision, Computer vision technology, Sensors, Antennas, Feature extraction, Data processing, Gaussian filters, Data modeling, Computing systems

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Proceedings Article | 3 May 2017 Presentation + Paper

Learning improved pooling regions for the Histogram of Oriented Gradient (HOG) feature for buried threat detection in ground penetrating radar

Daniël Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 10182, 101820V (2017) https://doi.org/10.1117/12.2263108

KEYWORDS: Ground penetrating radar, Detection and tracking algorithms, Shape analysis, Image processing, Data modeling, Performance modeling, Visualization, Machine vision, Computer vision technology, Receivers

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Proceedings Article | 3 May 2017 Presentation + Paper

Improving convolutional neural networks for buried target detection in ground penetrating radar using transfer learning via pretraining

John Bralich, Daniël Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 10182, 101820X (2017) https://doi.org/10.1117/12.2263112

KEYWORDS: Data modeling, Convolutional neural networks, Detection and tracking algorithms, Detector arrays, Photovoltaic detectors

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Proceedings Article | 3 May 2016 Paper

Using queuing models to aid design and guide research effort for multimodality buried target detection systems

Jordan Malof, Leslie Collins

Proceedings Volume 9823, 98231K (2016) https://doi.org/10.1117/12.2224131

KEYWORDS: Systems modeling, Forward looking infrared, Target detection, Sensors, Performance modeling, General packet radio service, Detection and tracking algorithms, Data modeling, Sensor performance, Computing systems

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Proceedings Article | 3 May 2016 Paper

Attribute-driven transfer learning for detecting novel buried threats with ground-penetrating radar

Kenneth Colwell, Leslie Collins

Proceedings Volume 9823, 982319 (2016) https://doi.org/10.1117/12.2222495

KEYWORDS: Ground penetrating radar, Data modeling, Explosives detection, Explosives, Binary data, General packet radio service, Performance modeling, Target recognition, Receivers, Feature extraction

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Proceedings Article | 3 May 2016 Paper

A feature learning approach for classifying buried threats in forward looking ground penetrating radar data

Joseph Camilo, Jordan Malof, Leslie Collins

Proceedings Volume 9823, 98231I (2016) https://doi.org/10.1117/12.2223117

KEYWORDS: Ground penetrating radar, Data modeling, Image filtering, Radar, Target detection, Feature extraction, Detection and tracking algorithms, Associative arrays, Sensors, Visualization

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Proceedings Article | 3 May 2016 Paper

Algorithm development for deeply buried threat detection in GPR data

Daniël Reichman, Jordan Malof, Leslie Collins

Proceedings Volume 9823, 98231A (2016) https://doi.org/10.1117/12.2222593

KEYWORDS: Target detection, Ground penetrating radar, Algorithm development, Remote sensing, Detection and tracking algorithms, General packet radio service, Sensors, Data processing, Detector development, Signal attenuation

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Proceedings Article | 24 March 2016 Paper

Radiogenomics of glioblastoma: a pilot multi-institutional study to investigate a relationship between tumor shape features and tumor molecular subtype

Nicholas Czarnek, Kal Clark, Katherine Peters, Leslie Collins, Maciej Mazurowski

Proceedings Volume 9785, 97850V (2016) https://doi.org/10.1117/12.2217084

KEYWORDS: Magnetic resonance imaging, Diagnostics, Magnetism, Shape analysis, Cancer, Biology, Radiology, Feature extraction, Medicine, Image segmentation, Tumors, Receivers, Data archive systems, Statistical analysis

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Proceedings Article | 24 March 2016 Paper

Predicting outcomes in glioblastoma patients using computerized analysis of tumor shape: preliminary data

Maciej Mazurowski, Nicholas Czarnek, Leslie Collins, Katherine Peters, Kal Clark

Proceedings Volume 9785, 97852T (2016) https://doi.org/10.1117/12.2217098

KEYWORDS: Shape analysis, Magnetic resonance imaging, Statistical analysis, Brain, Medicine, Medical imaging, Feature extraction, Oncology, Tumors, Cancer, Radiology

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Proceedings Article | 22 May 2015 Paper

Recognizing subsurface target responses in ground penetrating radar data using convolutional neural networks

Rayn Sakaguchi, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 9454, 94541A (2015) https://doi.org/10.1117/12.2177747

KEYWORDS: General packet radio service, Neural networks, Sensors, Feature extraction, Visualization, Ground penetrating radar, Target recognition, Target detection, Error analysis, Convolutional neural networks

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Proceedings Article | 21 May 2015 Paper

Improving buried threat detection in ground-penetrating radar with transfer learning and metadata analysis

Kenneth Colwell, Peter Torrione, Kenneth Morton, Leslie Collins

Proceedings Volume 9454, 94541C (2015) https://doi.org/10.1117/12.2177940

KEYWORDS: General packet radio service, Ground penetrating radar, Signal processing, Target detection, Classification systems, Data modeling, Receivers, Image processing, Image classification, Binary data

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Proceedings Article | 21 May 2015 Paper

Target signature localization in GPR data by jointly estimating and matching templates

Daniël Reichman, Kenneth Morton, Jordan Malof, Leslie Collins, Peter Torrione

Proceedings Volume 9454, 945416 (2015) https://doi.org/10.1117/12.2176627

KEYWORDS: Land mines, General packet radio service, Data modeling, Detection and tracking algorithms, Target detection, Data analysis, Process modeling, Ground penetrating radar, Remote sensing, Sensors

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Proceedings Article | 21 May 2015 Paper

Leveraging robust principal component analysis to detect buried explosive threats in handheld ground-penetrating radar data

Dmitry Kalika, Mary Knox, Leslie Collins, Peter Torrione, Kenneth Morton

Proceedings Volume 9454, 94541D (2015) https://doi.org/10.1117/12.2177944

KEYWORDS: Detection and tracking algorithms, Target detection, General packet radio service, Sensors, Explosives, Principal component analysis, Ground penetrating radar, Data modeling, Algorithm development, Expectation maximization algorithms

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Proceedings Article | 15 May 2015 Paper

Clutter and target discrimination in forward-looking ground penetrating radar using sparse structured basis pursuits

Joseph Camilo, Jordan Malof, Peter Torrione, Leslie Collins, Kenneth Morton

Proceedings Volume 9454, 94540V (2015) https://doi.org/10.1117/12.2176491

KEYWORDS: Sensors, Antennas, General packet radio service, Radar, Polarization, Detection and tracking algorithms, Ground penetrating radar, Land mines, Image processing, Target detection

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Proceedings Article | 14 May 2015 Paper

Buried threat detection using a handheld ground penetrating radar system

Mary Knox, Peter Torrione, Leslie Collins, Kenneth Morton

Proceedings Volume 9454, 94540F (2015) https://doi.org/10.1117/12.2177812

KEYWORDS: Sensors, Detection and tracking algorithms, General packet radio service, Head-mounted displays, Mining, Expectation maximization algorithms, Feature extraction, Ground penetrating radar, Robotics, Principal component analysis

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Proceedings Article | 14 May 2015 Paper

A queuing model for designing multi-modality buried target detection systems: preliminary results

Jordan Malof, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 9454, 94540I (2015) https://doi.org/10.1117/12.2176610

KEYWORDS: Forward looking infrared, General packet radio service, Sensors, Systems modeling, Data modeling, Computing systems, Detection and tracking algorithms, Target detection, Cameras, Infrared sensors

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Proceedings Article | 13 June 2014 Paper

A novel algorithm for buried target detection evaluated on a collection of seismo-acoustic data

Jordan Malof, Mary Knox, Peter Torrione, Leslie Collins, Kenneth Morton

Proceedings Volume 9072, 907208 (2014) https://doi.org/10.1117/12.2053842

KEYWORDS: Target detection, Detection and tracking algorithms, Acoustics, Laser Doppler velocimetry, Data processing, Ferroelectric LCDs, Fourier transforms, Sensors, Blob detection, Doppler effect

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Proceedings Article | 13 June 2014 Paper

Fusion of forward looking infrared and ground penetrating radar for improved stopping distances in landmine detection

Jordan Malof, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 9072, 90720W (2014) https://doi.org/10.1117/12.2051444

KEYWORDS: General packet radio service, Forward looking infrared, Sensors, Standoff detection, Feature extraction, Detection and tracking algorithms, Data processing, Cameras, Ground penetrating radar, Land mines

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Proceedings Article | 29 May 2014 Paper

A robust Bayesian approach to target detection applied to explosive threat detection in handheld ground penetrating radar data

Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 9072, 90720R (2014) https://doi.org/10.1117/12.2050514

KEYWORDS: Detection and tracking algorithms, General packet radio service, Target detection, Algorithm development, Statistical analysis, Data modeling, Ground penetrating radar, Radar, Sensors, Explosives

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Proceedings Article | 29 May 2014 Paper

Hyperbolic and PLSDA filter algorithms to detect buried threats in GPR data

Dmitry Kalika, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 9072, 90720U (2014) https://doi.org/10.1117/12.2050502

KEYWORDS: Detection and tracking algorithms, General packet radio service, Explosives, Target detection, Ground penetrating radar, Algorithm development, Gaussian pulse, Phase shifts, Fusion energy, Sensors

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Proceedings Article | 29 May 2014 Paper

Target detection and identification using synthetic aperture acoustics

Mary Knox, Stacy Tantum, Leslie Collins

Proceedings Volume 9072, 907206 (2014) https://doi.org/10.1117/12.2050390

KEYWORDS: Current controlled current source, Target detection, Acoustics, Backscatter, Feature extraction, Image compression, Transceivers, Computer programming, Radar imaging, Synthetic aperture radar

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Proceedings Article | 29 May 2014 Paper

Target localization and signature extraction in GPR data using expectation-maximization and principal component analysis

Daniel Reichman, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 9072, 90720Q (2014) https://doi.org/10.1117/12.2049874

KEYWORDS: Land mines, General packet radio service, Principal component analysis, Data modeling, Target detection, Sensors, Expectation maximization algorithms, Detection and tracking algorithms, Distortion, Dielectrics

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Proceedings Article | 29 May 2014 Paper

Experiment design for measuring the probability of detection in remote sensing: how many objects and how many passes

Peter Torrione, Leslie Collins, Kenneth Morton

Proceedings Volume 9072, 90720M (2014) https://doi.org/10.1117/12.2049704

KEYWORDS: Target detection, Data modeling, Sensors, Detection and tracking algorithms, Remote sensing, General packet radio service, Systems modeling, Electromagnetic coupling, Sensing systems, Visualization

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Proceedings Article | 29 May 2014 Paper

Physics-based deformations of ground penetrating radar signals to improve the detection of buried explosives

Rayn Sakaguchi, Kennth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 9072, 90720P (2014) https://doi.org/10.1117/12.2049316

KEYWORDS: General packet radio service, Land mines, Dielectrics, Sensors, Data modeling, Ground penetrating radar, Antennas, Signal detection, Explosives, Target detection

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Proceedings Article | 7 June 2013 Paper

A novel framework for processing forward looking infrared imagery with application to buried threat detection

Jordan Malof, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8709, 87091D (2013) https://doi.org/10.1117/12.2016113

KEYWORDS: Forward looking infrared, Sensors, Cameras, Video, Detection and tracking algorithms, Image processing, Infrared cameras, Land mines, Sensing systems, Transform theory

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Proceedings Article | 7 June 2013 Paper

Application of image categorization methods for buried threat detection in GPR data

Rayn Sakaguchi, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8709, 87091P (2013) https://doi.org/10.1117/12.2016709

KEYWORDS: Land mines, General packet radio service, Fusion energy, Detection and tracking algorithms, Image processing, Sensors, Visualization, Data modeling, Feature extraction, Data processing

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Proceedings Article | 7 June 2013 Paper

Multiple instance hidden Markov models for GPR-based landmine detection

Achut Manandhar, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8709, 87091L (2013) https://doi.org/10.1117/12.2016401

KEYWORDS: Land mines, Data modeling, General packet radio service, Statistical modeling, Target detection, Feature extraction, Matrices, Image segmentation, Detection and tracking algorithms, Signal detection

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Proceedings Article | 7 June 2013 Paper

Sparse model inversion and processing of spatial frequency-domain electromagnetic induction sensor array data for improved landmine discrimination

Stacy Tantum, Kenneth Colwell, Waymond Scott, Peter Torrione, Leslie Collins, Kenneth Morton

Proceedings Volume 8709, 87091E (2013) https://doi.org/10.1117/12.2016063

KEYWORDS: Sensors, Data modeling, Land mines, Electromagnetic coupling, Mining, Model-based design, Surface plasmons, Electromagnetism, Target detection, Signal processing

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Proceedings Article | 25 May 2012 Paper

Rapid position estimation and tracking for autonomous driving

Patrick Wang, Peter Torrione, Leslie Collins, Kenneth Morton

Proceedings Volume 8387, 83871I (2012) https://doi.org/10.1117/12.919317

KEYWORDS: Roads, Cameras, Video, Image analysis, Data modeling, RGB color model, Statistical analysis, Televisions, Computer simulations, Particles

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Proceedings Article | 11 May 2012 Paper

Multiple instance learning for landmine detection using ground penetrating radar

Achut Manandhar, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8357, 835721 (2012) https://doi.org/10.1117/12.917947

KEYWORDS: Data modeling, Land mines, Process modeling, General packet radio service, Feature extraction, Algorithm development, Machine learning, Computer simulations, Detection and tracking algorithms, Ground penetrating radar

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Ground Penetrating Radar (GPR) has been extensively employed as a technology for the detection of subsurface buried threats. Although vehicular mounted GPRs generate data in three dimensions, alarm declarations are usually only available in the form of 2-D spatial coordinates. The uncertainty in the depth of the target in the three dimensional volume of data, and the difficulties associated with automatically localizing objects in depth, can adversely impact feature extraction and training in some detection algorithms. In order to mitigate the negative impact of uncertainty in target depth, several algorithms have been developed that extract features from multiple depth regions and utilize these feature vectors in classification algorithms to perform final mine/nonmine decisions. However, the uncertainty in object depth significantly complicates learning since features at the correct target depth are often significantly different from features at other depths but in the same volume. Multiple Instance Learning (MIL) is a type of supervised learning approach in which labels are available for a collection of feature vectors but not for individual samples, or in this application, depths. The goal of MIL is to classify new collections of vectors as they become available. This set-based learning method is applicable in the landmine detection problem because features that are extracted independently from several depth bins can be viewed as a set of unlabeled feature vectors, where the entire set either corresponds to a buried threat or a false alarm. In this work, a novel generative Dirichlet Process Gaussian mixture model for MIL is developed that automatically infers the number of mixture components required to model the underlying distributions of mine/non-mine signatures and performs classification using a likelihood ratio test. In this work, we show that the performance of the proposed approach for discriminating targets from non-targets in GPR data is promising.

Proceedings Article | 11 May 2012 Paper

Change-based threat detection in urban environments with a forward-looking camera

Kenneth Morton, Christopher Ratto, Jordan Malof, Michael Gunter, Leslie Collins, Peter Torrione

Proceedings Volume 8357, 83571M (2012) https://doi.org/10.1117/12.917721

KEYWORDS: Video, Cameras, Explosives, Distance measurement, Video processing, Detection and tracking algorithms, Environmental sensing, Land mines, Roads, Light sources and illumination

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Proceedings Article | 11 May 2012 Paper

Integration of lidar with the NIITEK GPR for improved performance on rough terrain

Christopher Ratto, Kenneth Morton, Ian McMichael, Brian Burns, William Clark, Leslie Collins, Peter Torrione

Proceedings Volume 8357, 83571U (2012) https://doi.org/10.1117/12.919119

KEYWORDS: General packet radio service, LIDAR, Land mines, Detection and tracking algorithms, Antennas, Metals, Target detection, Sensors, Prototyping, Global Positioning System

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Proceedings Article | 11 May 2012 Paper

Processing forward-looking data for anomaly detection: single-look, multi-look, and spatial classification

Jordan Malof, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8357, 83571O (2012) https://doi.org/10.1117/12.918447

KEYWORDS: Detection and tracking algorithms, Sensors, Forward looking infrared, Target detection, Algorithm development, Image filtering, Electronic filtering, Cameras, Data modeling, Explosives

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Proceedings Article | 11 May 2012 Paper

Investigation of the effects of operator technique on handheld sensor data for landmine detection

Stacy Tantum, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8357, 83571B (2012) https://doi.org/10.1117/12.919427

KEYWORDS: Sensors, Land mines, General packet radio service, Target detection, Statistical analysis, Ground penetrating radar, Dielectrics, Electromagnetism, Detection and tracking algorithms, Head

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Proceedings Article | 11 May 2012 Paper

Keypoint-based image processing for landmine detection in GPR data

Rayn Sakaguchi, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8357, 83571Z (2012) https://doi.org/10.1117/12.918361

KEYWORDS: Sensors, General packet radio service, Image processing, Land mines, Detection and tracking algorithms, Machine vision, Computer vision technology, Sensor performance, Object recognition, Corner detection

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Proceedings Article | 11 May 2012 Paper

A Bayesian method for discriminative context-dependent fusion of GPR-based detection algorithms

Christopher Ratto, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8357, 835723 (2012) https://doi.org/10.1117/12.919079

KEYWORDS: General packet radio service, Land mines, Detection and tracking algorithms, Data fusion, Feature extraction, Metals, Performance modeling, Ground penetrating radar, Sensors, Soil science

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Proceedings Article | 11 May 2012 Paper

Feature extraction and processing of spatial frequency-domain electromagnetic induction sensor data for improved landmine discrimination

Stacy Tantum, Kenneth Colwell, Kenneth Morton, Waymond Scott, Leslie Collins, Peter Torrione

Proceedings Volume 8357, 835708 (2012) https://doi.org/10.1117/12.919421

KEYWORDS: Sensors, Data modeling, Land mines, Electromagnetic coupling, Mining, Electromagnetism, Feature extraction, Target detection, Model-based design, Signal processing

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Proceedings Article | 4 June 2011 Paper

Signal processing for the detection of explosive residues on varying substrates using laser-induced breakdown spectroscopy

Kenneth Morton, Peter Torrione, Leslie Collins

Proceedings Volume 8018, 801817 (2011) https://doi.org/10.1117/12.885111

KEYWORDS: Laser induced breakdown spectroscopy, Chemometrics, Data modeling, Principal component analysis, Explosives, Detection and tracking algorithms, Explosives detection, Binary data, Aluminum, Signal processing

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Proceedings Article | 3 June 2011 Paper

Classification of acoustic gunshot signatures using a nonparametric Bayesian signal model

Kenneth Morton, Peter Torrione, Leslie Collins

Proceedings Volume 8019, 80190T (2011) https://doi.org/10.1117/12.885114

KEYWORDS: Autoregressive models, Acoustics, Data modeling, Weapons, Statistical analysis, Firearms, Signal detection, Statistical modeling, Performance modeling, Time-frequency analysis

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Proceedings Article | 23 May 2011 Paper

Physics-based features for identifying contextual factors affecting landmine detection with ground-penetrating radar

Christopher Ratto, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8017, 80171Q (2011) https://doi.org/10.1117/12.884868

KEYWORDS: General packet radio service, Dielectrics, Land mines, Reflection, Finite-difference time-domain method, Feature extraction, Data modeling, Computer simulations, Ground penetrating radar, Environmental sensing

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Proceedings Article | 23 May 2011 Paper

Change detection for detecting potential threats in forward-looking video and downward-looking ground-penetrating radar data

Peter Torrione, Kenneth Morton, Christopher Ratto, Michael Gunter, Leslie Collins

Proceedings Volume 8017, 801721 (2011) https://doi.org/10.1117/12.884122

KEYWORDS: Video, General packet radio service, Roads, Land mines, Cameras, Video processing, Explosives, Feature extraction, Ground penetrating radar, Sensors

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Proceedings Article | 23 May 2011 Paper

Multiple instance learning framework for landmine detection using ground-penetrating radar

A. Manandhar, K. Morton, L. Collins, P. Torrione

Proceedings Volume 8017, 80171R (2011) https://doi.org/10.1117/12.884869

KEYWORDS: Land mines, General packet radio service, Feature extraction, Expectation maximization algorithms, Molecules, Ground penetrating radar, Machine learning, Sensors, Data acquisition, Target detection

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Proceedings Article | 23 May 2011 Paper

Contextual learning in ground-penetrating radar data using Dirichlet process priors

Christopher Ratto, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8017, 80171S (2011) https://doi.org/10.1117/12.884872

KEYWORDS: General packet radio service, Data modeling, Land mines, Detection and tracking algorithms, Process modeling, Performance modeling, Ground penetrating radar, Feature selection, 3D modeling, Data processing

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Proceedings Article | 23 May 2011 Paper

The Viterbi algorithm as an approach for incorporating spatial information into air/ground interface inference in GPR data

Peter Torrione, Kenneth Morton, Leslie Collins

Proceedings Volume 8017, 80171H (2011) https://doi.org/10.1117/12.884875

KEYWORDS: General packet radio service, Detection and tracking algorithms, Interfaces, Algorithm development, Ground penetrating radar, Land mines, Radar, Target detection, Explosives, Data processing

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Proceedings Article | 23 May 2011 Paper

Frequency domain electromagnetic induction sensor data feature extraction and processing for improved landmine detection

Stacy Tantum, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8017, 80170B (2011) https://doi.org/10.1117/12.884769

KEYWORDS: Data modeling, Sensors, Land mines, Signal to noise ratio, Target detection, Mining, Electromagnetic coupling, Distance measurement, Model-based design, Electromagnetism

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Proceedings Article | 23 May 2011 Paper

Exploiting spectral content for image segmentation in GPR data

Patrick Wang, Kenneth Morton, Leslie Collins, Peter Torrione

Proceedings Volume 8017, 80171T (2011) https://doi.org/10.1117/12.884874

KEYWORDS: General packet radio service, Image segmentation, Land mines, Feature extraction, Image processing algorithms and systems, Detection and tracking algorithms, Data processing, Sensors, Image filtering, Ground penetrating radar

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Proceedings Article | 23 May 2011 Paper

Comparison of algorithms for finding the air-ground interface in ground penetrating radar signals

Joshua Wood, Jeremy Bolton, George Casella, Leslie Collins, Paul Gader, Taylor Glenn, Jeffery Ho, Wen Lee, Richard Mueller, Brandon Smock, Peter Torrione, Ken Watford, Joseph Wilson

Proceedings Volume 8017, 80171L (2011) https://doi.org/10.1117/12.884201

KEYWORDS: Detection and tracking algorithms, Land mines, Antennas, General packet radio service, Ground penetrating radar, Interfaces, Algorithm development, Reflection, Sensors, Data corrections

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Proceedings Article | 29 April 2010 Paper

Nonparametric Bayesian time-series modeling and clustering of time-domain ground penetrating radar landmine responses

Kenneth Morton, Peter Torrione, Leslie Collins

Proceedings Volume 7664, 76642H (2010) https://doi.org/10.1117/12.850335

KEYWORDS: Autoregressive models, Land mines, Data modeling, Time-frequency analysis, General packet radio service, Statistical modeling, Statistical analysis, Mining, Ground penetrating radar, Expectation maximization algorithms

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Proceedings Article | 29 April 2010 Paper

Context-dependent feature selection using unsupervised contexts applied to GPR-based landmine detection

Christopher Ratto, Peter Torrione, Leslie Collins

Proceedings Volume 7664, 76642I (2010) https://doi.org/10.1117/12.850906

KEYWORDS: General packet radio service, Land mines, Feature extraction, Data modeling, Autoregressive models, Feature selection, Fourier transforms, Detection and tracking algorithms, Soil science, Reflection

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Proceedings Article | 29 April 2010 Paper

Fusion of ground-penetrating radar and electromagnetic induction sensors for landmine detection and discrimination

Mark Kolba, Peter Torrione, Leslie Collins

Proceedings Volume 7664, 76641S (2010) https://doi.org/10.1117/12.851364

KEYWORDS: Electromagnetic coupling, General packet radio service, Sensors, Land mines, Target detection, Model-based design, Fusion energy, Ground penetrating radar, Electromagnetism, Data fusion

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Proceedings Article | 29 April 2010 Paper

Sparse model representations of target signatures for improved landmine detection using frequency-domain electromagnetic induction sensors

Stacy Tantum, Peter Torrione, Leslie Collins

Proceedings Volume 7664, 76640D (2010) https://doi.org/10.1117/12.851378

KEYWORDS: Sensors, Data modeling, Land mines, Mining, Electromagnetic coupling, Target detection, Model-based design, Target recognition, Electromagnetism, Signal processing

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Proceedings Article | 29 April 2010 Paper

Information-based sensor management for the intelligent tasking of ground penetrating radar and electromagnetic induction sensors in landmine detection pre-screening

Mark Kolba, Leslie Collins

Proceedings Volume 7664, 766429 (2010) https://doi.org/10.1117/12.851360

KEYWORDS: Sensors, Electromagnetic coupling, Data modeling, General packet radio service, Land mines, Target detection, Affine motion model, Sensor performance, Ground penetrating radar, Electromagnetism

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Proceedings Article | 5 May 2009 Paper

Bayesian detection of acoustic muzzle blasts

Kenneth Morton, Leslie Collins

Proceedings Volume 7305, 730511 (2009) https://doi.org/10.1117/12.818547

KEYWORDS: Autoregressive models, Acoustics, Signal detection, Data modeling, Detection and tracking algorithms, Statistical analysis, Signal processing, Sensors, Error analysis, Statistical modeling

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Proceedings Article | 5 May 2009 Paper

Real-time Gaussian Markov random-field-based ground tracking for ground penetrating radar data

Kyle Bradbury, Peter Torrione, Leslie Collins

Proceedings Volume 7303, 730320 (2009) https://doi.org/10.1117/12.818781

KEYWORDS: Interfaces, General packet radio service, Detection and tracking algorithms, Sensors, Ground penetrating radar, Land mines, Antennas, Target detection, Statistical modeling, Statistical analysis

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Proceedings Article | 5 May 2009 Paper

A graphical user interface for real-time spectroscopy: software architecture for data collection, feature extraction, model development, and real-time testing

Peter Torrione, Kenneth Morton, Chris Lunsford, Leslie Collins

Proceedings Volume 7303, 73031I (2009) https://doi.org/10.1117/12.821726

KEYWORDS: Spectroscopy, Visualization, Data modeling, Algorithm development, Human-machine interfaces, Sensors, Feature extraction, Software development, MATLAB, Binary data

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Proceedings Article | 5 May 2009 Paper

Sensor management using a new framework for observation modeling

Mark Kolba, Leslie Collins

Proceedings Volume 7303, 730326 (2009) https://doi.org/10.1117/12.818829

KEYWORDS: Sensors, Magnetometers, Data modeling, Magnetic sensors, Sensor performance, Target detection, Binary data, Land mines, Electromagnetic coupling, Visual process modeling

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Proceedings Article | 5 May 2009 Paper

Context-dependent feature selection for landmine detection with ground-penetrating radar

Christopher Ratto, Peter Torrione, Leslie Collins

Proceedings Volume 7303, 730327 (2009) https://doi.org/10.1117/12.817946

KEYWORDS: General packet radio service, Autoregressive models, Land mines, Feature extraction, Feature selection, Detection and tracking algorithms, Environmental sensing, Data modeling, Antennas, Ground penetrating radar

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Proceedings Article | 29 April 2008 Paper

Performance comparison of frequency domain quadrupole and dipole electromagnetic induction sensors in a landmine detection application

Eric Fails, Peter Torrione, Waymond Scott, Leslie Collins

Proceedings Volume 6953, 695304 (2008) https://doi.org/10.1117/12.778898

KEYWORDS: Sensors, Land mines, Electromagnetic coupling, Sensor performance, Electromagnetism, Detection and tracking algorithms, Metals, Mining, Platinum, Signal to noise ratio

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Proceedings Article | 29 April 2008 Paper

Sensor management for landmine detection using correlated sensor observations

Mark Kolba, Leslie Collins

Proceedings Volume 6953, 695315 (2008) https://doi.org/10.1117/12.777707

KEYWORDS: Sensors, Data modeling, Performance modeling, Sensor performance, Binary data, Palladium, Land mines, Statistical analysis, Mathematical modeling, Target detection

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Proceedings Article | 29 April 2008 Paper

Application of Markov random fields to landmine detection in ground penetrating radar data

Peter Torrione, Leslie Collins

Proceedings Volume 6953, 69531B (2008) https://doi.org/10.1117/12.777746

KEYWORDS: Data modeling, General packet radio service, Statistical modeling, Statistical analysis, Land mines, Dielectrics, Magnetorheological finishing, Ground penetrating radar, Electromagnetism, Autoregressive models

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Recent advances in ground penetrating radar (GPR) design and fabrication have resulted in improved fidelity responses from relatively small, shallow-buried objects like landmines and improvised explosive devices. As the responses measured with GPR improve, more and more advanced processing techniques can be brought to bear on the problem of target identification in GPR data. From an electromagnetic point of view, the problem of target detection in GPR signal processing is reducible to inferring the presence or absence of changes in the electromagnetic properties of soils and thus the presence or absence of buried targets. Problems arise because the algorithms required for the full electromagnetic inversion of GPR signals are extremely computationally expensive, and usually rely on assumptions of electromagnetically constant transmission media; these problems typically make the real-time implementation of purely electromagnetic-inspired algorithms infeasible. On the other hand, purely statistical or signal-processing inspired approaches to target identification in GPR often lack a solid theoretical basis in the underlying physics, which is fundamental to understanding responses in GPR. In this work, we propose a model for responses in time-domain ground penetrating radar that attempts to incorporate the underlying physics of the problem, but avoids several of the issues inherent in assuming constant media with known electrical parameters by imposing a statistical model over the observed parameters of interest in A-scans - namely the signal gains, times of arrival, etc. The spatial requirements of the proposed statistical model suggests the application of Markov random field (MRF) distributions which provide expressive, but computationally simple models of spatial interactions. In this work we will explore the application of physics-based MRF's as generative models for time-domain GPR data, the pre-screening algorithms that this model motivates, and discuss how the model can be extended to other applications in GPR processing. Preliminary results showing how the MRF approach to understanding the underlying physics can improve performance are also shown.

Proceedings Article | 27 April 2007 Paper

Managing landmine detection sensors: results from application to AMDS data

Mark Kolba, Leslie Collins

Proceedings Volume 6553, 65531Y (2007) https://doi.org/10.1117/12.718457

KEYWORDS: Sensors, Data modeling, General packet radio service, Electromagnetic coupling, Land mines, Target detection, Sensor performance, Performance modeling, Binary data, Error analysis

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Proceedings Article | 27 April 2007 Paper

Performance of a four parameter model for modeling landmine signatures in frequency domain wideband electromagnetic induction detection systems

Eric Fails, Peter Torrione, Waymond Scott, Leslie Collins

Proceedings Volume 6553, 65530D (2007) https://doi.org/10.1117/12.719460

KEYWORDS: Sensors, Land mines, Data modeling, Electromagnetic coupling, Mining, Electromagnetism, Systems modeling, Performance modeling, Detection and tracking algorithms, Feature extraction

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Proceedings Article | 27 April 2007 Paper

Image segmentation techniques for improved processing of landmine responses in ground-penetrating radar data

Peter Torrione, Leslie Collins

Proceedings Volume 6553, 655329 (2007) https://doi.org/10.1117/12.718128

KEYWORDS: Land mines, General packet radio service, Image segmentation, Feature extraction, Magnetorheological finishing, Image processing, Ground penetrating radar, Radar, Sensors, Expectation maximization algorithms

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Proceedings Article | 27 April 2007 Paper

Ground bounce tracking for landmine detection using a sequential Monte Carlo method

Li Tang, Peter Torrione, Cihat Eldeniz, Leslie Collins

Proceedings Volume 6553, 655325 (2007) https://doi.org/10.1117/12.718462

KEYWORDS: Land mines, General packet radio service, Detection and tracking algorithms, Data modeling, Filtering (signal processing), Radar, Error analysis, Statistical modeling, Sensors, Systems modeling

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Proceedings Article | 18 May 2006 Paper

Comparison of pattern recognition approaches for multisensor detection and discrimination of anti-personnel and anti-tank landmines

Peter Torrione, Jeremiah Remus, Leslie Collins

Proceedings Volume 6217, 62172S (2006) https://doi.org/10.1117/12.665660

KEYWORDS: Electromagnetic coupling, General packet radio service, Land mines, Sensors, Feature extraction, Signal processing, Image classification, Pattern recognition, Ground penetrating radar, Metals

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Proceedings Article | 18 May 2006 Paper

Constrained filter optimization for subsurface landmine detection

Peter Torrione, Leslie Collins, Fred Clodfelter, Dan Lulich, Ajay Patrikar, Peter Howard, Richard Weaver, Erik Rosen

Proceedings Volume 6217, 62172X (2006) https://doi.org/10.1117/12.665780

KEYWORDS: Land mines, Autoregressive models, General packet radio service, Digital filtering, Genetic algorithms, Data modeling, Signal processing, Electronic filtering, Detection and tracking algorithms, Optimization (mathematics)

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Proceedings Article | 18 May 2006 Paper

The effects of uncertainty and uncertainty modeling on information-based sensor management performance

Mark Kolba, Leslie Collins

Proceedings Volume 6217, 62172U (2006) https://doi.org/10.1117/12.665595

KEYWORDS: Sensors, Sensor performance, Performance modeling, Land mines, Palladium, Mathematical modeling, Data modeling, Target detection, Vegetation, Research management

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Proceedings Article | 10 June 2005 Paper

Multi-modal iterative adaptive processing (MIAP) performance in the discrimination mode for landmine detection

Yongli Yu, Leslie Collins

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.603848

KEYWORDS: Sensors, Electromagnetic coupling, General packet radio service, Land mines, Detection and tracking algorithms, Mining, Sensor fusion, Target detection, Palladium, Data fusion

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Proceedings Article | 10 June 2005 Paper

Feature selection for physics model based object discrimination

Chunmei Wang, Leslie Collins

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.603451

KEYWORDS: Feature selection, Electromagnetic coupling, Data modeling, Sensors, Physics, Expectation maximization algorithms, Detection and tracking algorithms, Target detection, Electromagnetism, Feature extraction

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Proceedings Article | 10 June 2005 Paper

Application of matched subspace detectors to target detection and identification in ground penetrating radar data

Peter Torrione, Chandra Throckmorton, Leslie Collins, Fred Clodfelter, Shane Frasier, Ian Starnes, Steven Bishop, Peter Gugino, Peter Howard, Richard Weaver, Erik Rosen

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.602754

KEYWORDS: Sensors, Target detection, Land mines, Ground penetrating radar, Radar, General packet radio service, Signal detection, Detection and tracking algorithms, Target recognition, Data modeling

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Proceedings Article | 10 June 2005 Paper

Information-based sensor management for landmine detection using multimodal sensors

Mark Kolba, Peter Torrione, Leslie Collins

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.603582

KEYWORDS: Sensors, Land mines, Sensor performance, Active sensors, Target detection, Detection and tracking algorithms, General packet radio service, Electromagnetic coupling, Binary data, Computer simulations

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Proceedings Article | 10 June 2005 Paper

Analysis of wideband EMI field data

B. Whitecotton, T. McManus, S. Kuhn, Y. Dalichaouch, L. Carin, Pete Torrione, L. Collins

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.604191

KEYWORDS: Sensors, Target detection, Electromagnetic coupling, Metals, Land mines, Data acquisition, Mining, Calibration, Prototyping, Signal to noise ratio

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Proceedings Article | 10 June 2005 Paper

Force protection demining system (FPDS) detection subsystem

Karen Zachery, Gregory Schultz, Leslie Collins

Proceedings Volume 5794, (2005) https://doi.org/10.1117/12.603021

KEYWORDS: Electromagnetic coupling, Sensors, Target detection, Land mines, Detection and tracking algorithms, Data fusion, Feature extraction, Nonmetals, Feature selection, Data acquisition

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Proceedings Article | 21 September 2004 Paper

Man versus machine: robust regional processing of EMI data

Lisa Huettel, Jamie Baier, Leslie Collins

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.541601

KEYWORDS: Sensors, Detection and tracking algorithms, Mining, Metals, Robotics, Land mines, Electromagnetic coupling, Algorithm development, Signal processing, Sensor performance

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Proceedings Article | 21 September 2004 Paper

Parameterized likelihood ratio method for EMI unexploded ordnance detection

Harry Marr, Peter Torrione, Jonathan Miller, Leslie Collins

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.542297

KEYWORDS: Electromagnetic coupling, Sensors, Data modeling, Databases, Filtering (signal processing), Electromagnetism, Signal processing, Interference (communication), Target detection, Nose

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Proceedings Article | 21 September 2004 Paper

The efficacy of human observation for discrimination and feature identification of targets measured by the NIITEK ground-penetrating radar

Chandra Throckmorton, Peter Torrione, Leslie Collins, Paul Gader, Wen-Hsiung Lee, Joseph Wilson

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.541168

KEYWORDS: Land mines, Mining, General packet radio service, Ground penetrating radar, Palladium, Detection and tracking algorithms, Radar, Visualization, Algorithm development, Antennas

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Proceedings Article | 21 September 2004 Paper

Three-dimensional features to improve detection using ground-penetrating radar

David Lang, Brian Dustin, Peter Torrione, Leslie Collins

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.542946

KEYWORDS: Mining, General packet radio service, Ground penetrating radar, Land mines, Antennas, 3D modeling, Reflectors, Data modeling, Radar, Dielectrics

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Proceedings Article | 21 September 2004 Paper

Feature-based processing of prescreener-generated alarms for performance improvements in target identification using the NIITEK ground-penetrating radar system

Peter Torrione, Chandra Throckmorton, Leslie Collins, J. Clodfelter, Shane Frasier, Ian Starnes, Steven Bishop, Peter Gugino, Peter Howard, Richard Weaver, Erik Rosen

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.540926

KEYWORDS: General packet radio service, Detection and tracking algorithms, Land mines, Roads, Target recognition, Ground penetrating radar, Receivers, Sensors, Hough transforms, Image classification

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Proceedings Article | 21 September 2004 Paper

Landmine discrimination via Bayesian adaptive multimodal processing: results for handheld and vehicular sensors

Yongli Yu, Peter Torrione, Leslie Collins

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.542276

KEYWORDS: Sensors, General packet radio service, Metals, Land mines, Detection and tracking algorithms, Electromagnetic coupling, Mining, Sensor fusion, Algorithm development, Fusion energy

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Proceedings Article | 21 September 2004 Paper

Signal processing for improved explosives detection using quadrupole resonance

Yingyi Tan, Stacy Tantum, Leslie Collins

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.542553

KEYWORDS: Electromagnetic coupling, Filtering (signal processing), Autoregressive models, Data modeling, Signal detection, Electronic filtering, Signal processing, Interference (communication), Explosives detection, Explosives

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Proceedings Article | 21 September 2004 Paper

Data analysis for classification of UXO filler using pulsed-neutron techniques

Giancarlo Borgonovi, Daniel Holslin, Leslie Collins, Stacy Tantum

Proceedings Volume 5415, (2004) https://doi.org/10.1117/12.542288

KEYWORDS: Principal component analysis, Explosives, Data analysis, Gamma radiation, Sensors, Data modeling, Statistical analysis, Data processing, Calibration, Pattern recognition

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