Presentation + Paper
30 May 2022 Explosive hazard pre-screener based on simulated data with perfect annotation and imprecisely labeled real data
Author Affiliations +
Abstract
Datasets with accurate ground truth from unmanned aerial vehicles (UAV) are cost and time prohibitive. This is a problem as most modern machine learning (ML) algorithms are based on supervised learning and require large and diverse well-annotated datasets. As a result, new creative ideas are needed to drive innovation in robust and trustworthy artificial intelligence (AI) / ML. Herein, we use the Unreal Engine (UE) to generate simulated visual spectrum imagery for explosive hazard detection (EHD) with corresponding pixel-level labels, UAV metadata, and environment metadata. We also have access to a relatively small set of real world EH data with less precise ground truth – axis aligned bounding box labels – and sparse metadata. In this article, we train a lightweight, real-time, pixel-level EHD pre-screener for a low-altitude UAV. Specifically, we focus on training with respect to different combinations of simulated and real data. Encouraging preliminary results are provided relative to real world EH data. Our findings suggest that while simulated data can be used to augment limited volume and variety real world data, it could perhaps be sufficient by itself to train an EHD pre-screener.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Madeline Kovaleski, Aaron Fuller, Jeffrey Kerley, Brendan J. Alvey, Peter Popescu, Derek Anderson, Andrew Buck, James Keller, Grant Scott, Clare Yang, Ken E. Yasuda, and Hollie A. Ryan "Explosive hazard pre-screener based on simulated data with perfect annotation and imprecisely labeled real data", Proc. SPIE 12116, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XXIII, 121160X (30 May 2022); https://doi.org/10.1117/12.2618792
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Computer simulations

Data modeling

Unmanned aerial vehicles

Image segmentation

Explosives

RGB color model

3D modeling

Back to Top