Learning improved pooling regions for the Histogram of Oriented Gradient (HOG) feature for buried threat detection in ground penetrating radar-Reference-Cited by-同舟云学术

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

Published:2017-05-03 Issue: Volume: Page:
ISSN:0277-786X
Container-title:SPIE Proceedings
language:
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Author:

Reichman Daniël¹,Collins Leslie M.¹,Malof Jordan M.¹

Affiliation:

1. Duke Univ. (United States)

Publisher

SPIE

Reference40 articles.

1. Performance of a Four Parameter Model for Modeling Landmine Signatures in Frequency Domain Wideband Electromagnetic Induction Detection Systems;Fails;Proc. SPIE,2007

2. Soil properties and performance of landmine detection by metal detector and ground-penetrating radar — Soil characterisation and its verification by a field test

3. Fusion of forward-looking infrared camera and down-looking ground penetrating radar for buried target detection;Yuksel;SPIE Defense+Secur.,2015

4. Clutter and target discrimination in forward-looking ground penetrating radar using sparse structured basis pursuits;Camilo,2015

5. Automatic detection system for buried explosive hazards in FL-LWIR based on soft feature extraction using a bank of Gabor energy filters;Price;SPIE Defense+Secur.,2013

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