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Convolutional neural network based side attack explosive hazard detection in three dimensional voxel radar
Author(s): Blake Brockner; Charlie Veal; Joshua Dowdy; Derek T. Anderson; Kathryn Williams; Robert Luke; David Sheen
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Paper Abstract

The identification followed by avoidance or removal of explosive hazards in past and/or present conflict zones is a serious threat for both civilian and military personnel. This is a challenging task as variability exists with respect to the objects, their environment and emplacement context, to name a few factors. A goal is the development of automatic or human-in-the-loop sensor technologies that leverage signal processing, data fusion and machine learning. Herein, we explore the detection of side attack explosive hazards (SAEHs) in three dimensional voxel space radar via different shallow and deep convolutional neural network (CNN) architectures. Dimensionality reduction is performed by using multiple projected images versus the raw three dimensional voxel data, which leads to noteworthy savings in input size and associated network hyperparameters. Last, we explore the accuracy and interpretation of solutions learned via random versus intelligent network weight initialization. Experiments are provided on a U.S. Army data set collected over different times, weather conditions, target types and concealments. Preliminary results indicate that deep learning can perform as good as, if not better, than a skilled domain expert, even in light of limited training data with a class imbalance.

Paper Details

Date Published: 30 April 2018
PDF: 13 pages
Proc. SPIE 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII, 106281H (30 April 2018); doi: 10.1117/12.2304507
Show Author Affiliations
Blake Brockner, Mississippi State Univ. (United States)
Charlie Veal, Mississippi State Univ. (United States)
Joshua Dowdy, Mississippi State Univ. (United States)
Derek T. Anderson, Univ. of Missouri (United States)
Kathryn Williams, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Robert Luke, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
David Sheen, Pacific Northwest National Lab. (United States)


Published in SPIE Proceedings Vol. 10628:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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