Prof. Jordan M. Malof Profile

Prof. Jordan M. Malof

SPIE Involvement:

Author

Publications (26)

Proceedings Article | 3 August 2021 Presentation

Deep learning and inverse design of artificial electromagnetic materials

Willie Padilla, Yang Deng, Simiao Ren, Jordan Malof

Proceedings Volume 11795, 1179504 (2021) https://doi.org/10.1117/12.2593081

KEYWORDS: Electromagnetism, Neural networks, Plasmonics, Photonic crystals, Optimization (mathematics), Inverse problems, Gallium antimonide, External quantum efficiency, Electromagnetic metamaterials

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Proceedings Article | 24 April 2020 Presentation + Paper

How robust are deep object detectors to variability in ground truth bounding boxes? Experiments for target recognition in infrared imagery

Evan Stump, Francisco Reveriano, Leslie Collins, Jordan Malof

Proceedings Volume 11394, 1139418 (2020) https://doi.org/10.1117/12.2565897

KEYWORDS: Data modeling, Infrared imaging, Target detection, Visualization, Performance modeling, Sensors, Infrared radiation, Video, Target recognition, Mathematical modeling

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Proceedings Article | 10 May 2019 Presentation + Paper

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

Evan Stump, Daniel Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 11012, 110120F (2019) https://doi.org/10.1117/12.2519949

KEYWORDS: Algorithm development, General packet radio service, Sensors, Detection and tracking algorithms, Ground penetrating radar, Feature extraction, Radar, Antennas, Image filtering, Reflection

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Proceedings Article | 10 May 2019 Presentation + Paper

Reliable training of convolutional neural networks for GPR-based buried threat detection using the Adam optimizer and batch normalization

Steven Jacobson, Daniël Reichman, Joel Bjornstad, Leslie Collins, Jordan Malof

Proceedings Volume 11012, 1101206 (2019) https://doi.org/10.1117/12.2519798

KEYWORDS: General packet radio service, Convolutional neural networks, Detection and tracking algorithms, Neurons, Control systems, Performance modeling, Data processing, Algorithm development, Data modeling, Network architectures

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Proceedings Article | 10 May 2019 Presentation + Paper

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

Evan Stump, Daniel Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 11012, 110120G (2019) https://doi.org/10.1117/12.2519969

KEYWORDS: Algorithm development, General packet radio service, Detection and tracking algorithms, Sensors, Ground penetrating radar, Antennas, Feature extraction, Data modeling, Radar, Systems modeling

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Proceedings Article | 30 April 2018 Presentation + Paper

How do we choose the best model? The impact of cross-validation design on model evaluation for buried threat detection in ground penetrating radar

Jordan Malof, Daniël Reichman, Leslie Collins

Proceedings Volume 10628, 106280C (2018) https://doi.org/10.1117/12.2305793

KEYWORDS: Detection and tracking algorithms, Data modeling, Ground penetrating radar, Algorithm development, Data processing, Feature extraction, Visual process modeling, Unexploded object detection, Threat warning systems

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Proceedings Article | 30 April 2018 Presentation + Paper

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

Jordan Malof, John Bralich, Daniël Reichman, Leslie Collins

Proceedings Volume 10628, 106280D (2018) https://doi.org/10.1117/12.2305797

KEYWORDS: General packet radio service, Feature extraction, Neural networks, Convolutional neural networks, Algorithm development, Ground penetrating radar, Detection and tracking algorithms, Data processing, Data modeling, Object recognition

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Proceedings Article | 30 April 2018 Paper

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

Daniël Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 10628, 106280E (2018) https://doi.org/10.1117/12.2305880

KEYWORDS: Visualization, General packet radio service, Algorithm development, Feature extraction, Computer programming, Ground penetrating radar, Detection and tracking algorithms, Radar imaging, Sensors, Data processing

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Proceedings Article | 30 April 2018 Paper

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

Daniël Reichman, Leslie Collins, Jordan Malof

Proceedings Volume 10628, 106280F (2018) https://doi.org/10.1117/12.2305881

KEYWORDS: General packet radio service, Machine learning, Data analysis, Algorithm development, Detection and tracking algorithms, Data modeling, Ground penetrating radar, Visualization, Antennas, Feature extraction

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