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

Mapping Intimacies ◽

10.1117/12.2263108 ◽

2017 ◽

Author(s):

Daniël Reichman ◽

Leslie M. Collins ◽

Jordan M. Malof

Keyword(s):

Ground Penetrating Radar ◽

Threat Detection ◽

Histogram Of Oriented Gradient ◽

Ground Penetrating

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

10.1117/12.2263107 ◽

2017 ◽

Cited By ~ 1

Author(s):

Daniël Reichman ◽

Leslie M. Collins ◽

Jordan M. Malof

Keyword(s):

Ground Penetrating Radar ◽

Radar Data ◽

Threat Detection ◽

Histogram Of Oriented Gradient ◽

Ground Penetrating

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

Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII ◽

10.1117/12.2305797 ◽

2018 ◽

Cited By ~ 1

Author(s):

Jordan M. Malof ◽

John Bralich ◽

Daniël Reichman ◽

Leslie M. Collins

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Ground Penetrating Radar ◽

Threat Detection ◽

Histogram Of Oriented Gradient ◽

Ground Penetrating ◽

Gradient Feature

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

10.1117/12.2050514 ◽

2014 ◽

Author(s):

Kenneth D. Morton ◽

Leslie M. Collins ◽

Peter A. Torrione

Keyword(s):

Target Detection ◽

Bayesian Approach ◽

Ground Penetrating Radar ◽

Radar Data ◽

Threat Detection ◽

Ground Penetrating

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Histogram of gradient features for buried threat detection in ground penetrating radar data

2012 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2012.6350748 ◽

2012 ◽

Cited By ~ 3

Author(s):

Peter Torrione ◽

Kenneth D. Morton ◽

Rayn Sakaguchi ◽

Leslie M. Collins

Keyword(s):

Ground Penetrating Radar ◽

Radar Data ◽

Threat Detection ◽

Ground Penetrating

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

Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII ◽

10.1117/12.2305881 ◽

2018 ◽

Author(s):

Daniël Reichman ◽

Leslie M. Collins ◽

Jordan M. Malof

Keyword(s):

Supervised Learning ◽

Ground Penetrating Radar ◽

Learning Algorithms ◽

Radar Data ◽

Training Data ◽

Threat Detection ◽

Supervised Learning Algorithms ◽

Ground Penetrating

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

Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII ◽

10.1117/12.2305880 ◽

2018 ◽

Cited By ~ 1

Author(s):

Daniël Reichman ◽

Leslie M. Collins ◽

Jordan M. Malof

Keyword(s):

Ground Penetrating Radar ◽

Radar Data ◽

Threat Detection ◽

Shape Information ◽

Ground Penetrating

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Buried threat detection using a handheld ground penetrating radar system

10.1117/12.2177812 ◽

2015 ◽

Author(s):

Mary Knox ◽

Peter Torrione ◽

Leslie Collins ◽

Kenneth Morton

Keyword(s):

Ground Penetrating Radar ◽

Radar System ◽

Threat Detection ◽

Ground Penetrating

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

Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV ◽

10.1117/12.2519949 ◽

2019 ◽

Author(s):

Evan Stump ◽

Daniël Reichman ◽

Leslie M. Collins ◽

Jordan M. Malof

Keyword(s):

Ground Penetrating Radar ◽

Threat Detection ◽

Gradient Based ◽

Ground Penetrating

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

Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV ◽

10.1117/12.2519969 ◽

2019 ◽

Author(s):

Evan Stump ◽

Daniël Reichman ◽

Leslie M. Collins ◽

Jordan M. Malof

Keyword(s):

Ground Penetrating Radar ◽

Radar Data ◽

Threat Detection ◽

Ground Penetrating

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The effect of translational variance in training and testing images on supervised buried threat detection algorithms for ground penetrating radar

2017 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR) ◽

10.1109/iwagpr.2017.7996104 ◽

2017 ◽

Author(s):

Daniel Reichman ◽

Leslie M. Collins ◽

Jordan M. Malof

Keyword(s):

Ground Penetrating Radar ◽

Threat Detection ◽

Detection Algorithms ◽

Ground Penetrating

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