Dr. Firooz A. Sadjadi
Senior Research Staff Scientist at
SPIE Involvement:
Fellow status | Conference Chair | Conference Program Committee | Conference Co-Chair | Editor | Author | Instructor
Publications (88)

SPIE Conference Volume | June 7, 2017

PROCEEDINGS ARTICLE | May 1, 2017
Proc. SPIE. 10202, Automatic Target Recognition XXVII
KEYWORDS: Visualization, Cameras, Sensors, Water, Image processing, Video, Video surveillance, Image registration, 3D metrology, Image enhancement

SPIE Conference Volume | August 11, 2016

PROCEEDINGS ARTICLE | May 12, 2016
Proc. SPIE. 9844, Automatic Target Recognition XXVI
KEYWORDS: Radar, 3D acquisition, Roentgenium, Data modeling, Scattering, Matrices, Pattern recognition, 3D modeling, Automatic target recognition, Chemical elements

PROCEEDINGS ARTICLE | June 19, 2015
Proc. SPIE. 9476, Automatic Target Recognition XXV
KEYWORDS: Target detection, Detection and tracking algorithms, Sensors, Mining, Fractal analysis, Associative arrays, Algorithm development, Environmental sensing, 3D image processing, Land mines

SPIE Conference Volume | June 2, 2015

Showing 5 of 88 publications
Conference Committee Involvement (52)
Automatic Target Recognition XXVIII
16 April 2018 | Orlando, Florida, United States
Automatic Target Recognition XXVII
10 April 2017 | Anaheim, California, United States
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2016
21 April 2016 | Baltimore, Maryland, United States
Automatic Target Recognition XXVI
18 April 2016 | Baltimore, Maryland, United States
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2015
21 April 2015 | Baltimore, Maryland, United States
Showing 5 of 52 published special sections
Course Instructor
SC158: Fundamentals of Automatic Target Recognition
This course is an overview of ATR systems, architecture, and components. Throughout the course various ATR sensors are discussed including: FLIR, SAR, LIDAR, and others. First, the course describes ATR system architecture. The course provides an overview of various ATR modules: preprocessing, image and signal enhancement, target detection, segmentation, feature extraction, and classifications. The course describes various features extraction techniques and classification methods, ranging from traditional statistical pattern recognition approaches to model-based techniques. The course presents an overview of advanced ATR concepts such as: multi-sensor systems, modeling and phenomenology, adaptive and neural net based methods, and other artificial intelligence techniques are described. Finally, we discuss evaluation techniques of ATR systems.
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