Prof. Dominic K.C. Ho Profile

Prof. Dominic K.C. Ho

Professor at Univ of Missouri

SPIE Involvement:

Author

Publications (58)

Proceedings Article | 14 June 2023 Presentation + Paper

Detection of curved wires by ground-penetrating radar

Jackson Moeller, Dominic K. Ho, Derek Anderson

Proceedings Volume 12541, 125410F (2023) https://doi.org/10.1117/12.2659568

KEYWORDS: Clutter, Edge detection, Hough transforms, Ground penetrating radar, Explosives, 3D image processing

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Proceedings Article | 14 June 2023 Poster + Paper

Improving ellipse feature for wire detection

Jackson Moeller, Dominic K. Ho, Derek Anderson

Proceedings Volume 12541, 125410R (2023) https://doi.org/10.1117/12.2659564

KEYWORDS: Hough transforms, Object detection, Image processing, Ground penetrating radar, Feature extraction

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Proceedings Article | 30 May 2022 Presentation + Paper

Exploring ellipse feature in GPR image for wire detection

Jackson Moeller, Dominic K. Ho, Derek Anderson

Proceedings Volume 12116, 1211615 (2022) https://doi.org/10.1117/12.2618674

KEYWORDS: Edge detection, Hough transforms, Image processing, 3D image processing, Sensors, Detection and tracking algorithms, Target detection, Remote sensing, Image filtering

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Proceedings Article | 12 April 2021 Presentation + Paper

Improving explosive hazard detection with simulated and augmented data for an unmanned aerial system

Brendan Alvey, Derek Anderson, James Keller, Andrew Buck, Grant Scott, Dominic Ho, Clare Yang, Brad Libbey

Proceedings Volume 11750, 117500B (2021) https://doi.org/10.1117/12.2586342

KEYWORDS: Explosives detection, Explosives, Environmental sensing, Machine learning, Sensors, Physics, Opacity, Infrared radiation, Infrared imaging, Fuzzy logic

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Proceedings Article | 12 April 2021 Presentation + Paper

Wire detection by GPR using the Hough transform

Jackson Moeller, Brendan Young, Dominic K. Ho, Derek Anderson

Proceedings Volume 11750, 1175005 (2021) https://doi.org/10.1117/12.2585854

KEYWORDS: Hough transforms, General packet radio service, Ground penetrating radar, Explosives

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Proceedings Article | 12 April 2021 Presentation + Paper

Metadata enabled contextual sensor fusion for unmanned aerial system-based explosive hazard detection

Matthew Deardorff, Brendan Alvey, Derek Anderson, James Keller, Grant Scott, Dominic Ho, Andrew Buck, Clare Yang, Brad Libbey

Proceedings Volume 11750, 117500C (2021) https://doi.org/10.1117/12.2586340

KEYWORDS: Explosives detection, Explosives, Sensor fusion, Electro optical modeling, Sensors, Machine learning, Physics, Intelligent sensors, Infrared sensors, Glasses

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Numerous real-world applications require the intelligent combining of disparate information streams from sensors to create a more complete and enhanced observation in support of underlying tasks like classification, regression, or decision making. An often overlooked and underappreciated part of fusion is context. Herein, we focus on two contextual fusion challenges, incomplete (limited knowledge) models and metadata. Examples of metadata available to unmanned aerial systems (UAS) include time of day, platform/sensor position, etc., all of which have a potentially drastic impact on sensor measurements and subsequently our decisions derived from them. Additionally, incomplete models limit machine learning, specifically under-sampling of training data. To address these challenges, we investigate contextually adaptive online Choquet integration. First, we cluster and partition the training metadata. Second, a single machine learning model is trained per partition. Third, a Choquet integral is learned for the combination of these models per partition. Fourth, at test/run time we compute the degree of typicality of a new sample to our known contexts. Fifth, our trained integrals are decomposed into a bag of underlying aggregation operators and a new contextually relevant operator is imputed using a combination of the metadata clustering and observation statistics of the integral variables. This process enables machine learning model selection, ensemble fusion, and metadata outlier detection, with subsequent mitigation strategy identification or decision suppression. The above ideas are demonstrated on explosive hazard detection using surrogate data simulated by the Unreal Engine. In particular, the Unreal Engine is used because it provides us with flexibility to explore the proposed ideas across a range of diverse and controlled experiments. Our preliminary results show improved performance for fusion in different contexts and a sensitivity analysis is performed with respect to metadata degradation.

Proceedings Article | 24 April 2020 Presentation + Paper

Extending deep learning to new classes without retraining

Jeffrey Schulz, Charlie Veal, Andrew Buck, Derek Anderson, James Keller, Mihail Popescu, Grant Scott, Dominic K. C. Ho, Timothy Wilkin

Proceedings Volume 11418, 1141803 (2020) https://doi.org/10.1117/12.2558134

KEYWORDS: Principal component analysis, Visualization, Matrices, Automatic target recognition, Feature extraction, Animal model studies, Explosives, Explosives detection, Data modeling, Artificial intelligence

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Proceedings Article | 24 April 2020 Presentation + Paper

Doing more with less: similarity neural nets and metrics for small class imbalanced data sets

Charlie Veal, Jeffrey Schulz, Andrew Buck, Derek Anderson, James Keller, Mihail Popescu, Grant Scott, Dominic Ho, Timothy Wilkin

Proceedings Volume 11418, 1141802 (2020) https://doi.org/10.1117/12.2558092

KEYWORDS: Data modeling, Prototyping, Visualization, Neural networks, Feature extraction, Statistical modeling, Performance modeling, Visual process modeling, Binary data, Image resolution

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Proceedings Article | 10 May 2019 Paper

On the use of multiresolution analysis for subsurface object detection using deep ground penetrating radar

Dominic K. Ho, Pooparat Plodpradista

Proceedings Volume 11012, 1101209 (2019) https://doi.org/10.1117/12.2519389

KEYWORDS: Target detection, Detection and tracking algorithms, Ground penetrating radar, Sensors, Analytical research, Fourier transforms, Time-frequency analysis

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Proceedings Article | 30 April 2018 Paper

Sample spacing variations on the feature performance for subsurface object detection using handheld ground penetrating radar

Brendan Alvey, Dominic K. Ho, Alina Zare

Proceedings Volume 10628, 106280U (2018) https://doi.org/10.1117/12.2303931

KEYWORDS: Target detection, Land mines, Ground penetrating radar, Sensors, Feature extraction, Explosives

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Proceedings Article | 30 April 2018 Paper

Analyzing three dimensional radar voxel data using the discrete Fourier transform for SAEH detection

P. Plodpradista, D. K. Ho, J. Keller, M. Popescu, A. Buck

Proceedings Volume 10628, 1062814 (2018) https://doi.org/10.1117/12.2304380

KEYWORDS: Fourier transforms, Radar, Feature extraction, Data modeling, Explosives, 3D image processing, Explosives detection, Sensors, Data processing

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Proceedings Article | 3 May 2017 Presentation + Paper

Tuning log Gabor filter bank using genetic algorithm based optimization

P. Plodpradista, J. Keller, D. K. Ho, M. Popescu

Proceedings Volume 10182, 101821C (2017) https://doi.org/10.1117/12.2262615

KEYWORDS: Image filtering, Filtering (signal processing), Radar, Image processing, Explosives, Electronic filtering, Genetic algorithms, Optimization (mathematics), Explosives detection, Target detection, Ground penetrating radar, Sensors, Roads, Vegetation

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Proceedings Article | 3 May 2017 Paper

Fourier features for explosive hazard detection using a wideband electromagnetic induction sensor

Brendan Alvey, Dominic K. Ho, Alina Zare

Proceedings Volume 10182, 101820E (2017) https://doi.org/10.1117/12.2263019

KEYWORDS: Explosives, Electromagnetism, Sensors, Electromagnetic coupling, Explosives detection, Land mines, Metals, Feature extraction, Fourier transforms, Detection and tracking algorithms, Target detection, Filtering (signal processing), Associative arrays

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Proceedings Article | 3 May 2017 Paper

LBP features for hand-held ground penetrating radar

Samuel Harris, Brendan Alvey, Dominic K. Ho, Alina Zare

Proceedings Volume 10182, 101820Z (2017) https://doi.org/10.1117/12.2263199

KEYWORDS: Radar, Detection and tracking algorithms, Sensors, Feature extraction, Explosives, Target detection, Ground penetrating radar

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Proceedings Article | 3 May 2016 Paper

Sequential feature selection for detecting buried objects using forward looking ground penetrating radar

Darren Shaw, Kevin Stone, K. C. Ho, James Keller, Robert Luke, Brian Burns

Proceedings Volume 9823, 98231L (2016) https://doi.org/10.1117/12.2224272

KEYWORDS: Feature extraction, Feature selection, Ground penetrating radar, Target detection, Radar, Image filtering, Polarization, Binary data, Metals, X band

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Proceedings Article | 3 May 2016 Paper

Buried object detection using handheld WEMI with task-driven extended functions of multiple instances

Matthew Cook, Alina Zare, Dominic Ho

Proceedings Volume 9823, 98230A (2016) https://doi.org/10.1117/12.2223349

KEYWORDS: Land mines, Associative arrays, Sensors, Detection and tracking algorithms, Metals, Data modeling, Electromagnetic coupling, Target detection, Expectation maximization algorithms, Algorithm development

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Proceedings Article | 3 May 2016 Paper

Adaptive coherence estimator (ACE) for explosive hazard detection using wideband electromagnetic induction (WEMI)

Brendan Alvey, Alina Zare, Matthew Cook, Dominic Ho

Proceedings Volume 9823, 982309 (2016) https://doi.org/10.1117/12.2223347

KEYWORDS: Explosives, Sensors, Statistical analysis, Explosives detection, Electromagnetism, Target detection, Associative arrays, Receivers, Detection and tracking algorithms, Statistical modeling

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Proceedings Article | 3 May 2016 Paper

On the use of log-gabor features for subsurface object detection using ground penetrating radar

Samuel Harris, K. C. Ho, Alina Zare

Proceedings Volume 9823, 98230K (2016) https://doi.org/10.1117/12.2223324

KEYWORDS: General packet radio service, Radar, Sensors, Ground penetrating radar, Metals, Target detection, Data modeling, Detection and tracking algorithms, Feature extraction, Molybdenum

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Proceedings Article | 21 May 2015 Paper

Anomaly detection of subsurface objects using handheld ground-penetrating radar

K. Ho, Samuel Harris, Alina Zare, Matthew Cook

Proceedings Volume 9454, 94541B (2015) https://doi.org/10.1117/12.2178584

KEYWORDS: Sensors, Detection and tracking algorithms, Target detection, General packet radio service, Data processing, Ground penetrating radar, Radar, Mahalanobis distance, Land mines, Metals

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Proceedings Article | 21 May 2015 Paper

Detection of deeply buried non-metal objects by ground penetrating radar using non-negative matrix factorization

Daniel Nabelek, K. Ho

Proceedings Volume 9454, 945419 (2015) https://doi.org/10.1117/12.2177481

KEYWORDS: Target detection, General packet radio service, Nonmetals, Detection and tracking algorithms, Ground penetrating radar, Sensors, Image enhancement, Signal detection, Matrices, Principal component analysis

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Proceedings Article | 15 May 2015 Paper

Explosive hazard detection using MIMO forward-looking ground penetrating radar

Darren Shaw, K. Ho, Kevin Stone, James Keller, Mihail Popescu, Derek Anderson, Robert Luke, Brian Burns

Proceedings Volume 9454, 94540Z (2015) https://doi.org/10.1117/12.2177468

KEYWORDS: Polarization, Image filtering, Feature extraction, Metals, Explosives, Target detection, Explosives detection, Radar, Ground penetrating radar, Nonmetals

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Proceedings Article | 14 May 2015 Paper

Multiple instance dictionary learning for subsurface object detection using handheld EMI

Alina Zare, Matthew Cook, Brendan Alvey, Dominic Ho

Proceedings Volume 9454, 94540G (2015) https://doi.org/10.1117/12.2179177

KEYWORDS: Associative arrays, Electromagnetic coupling, Expectation maximization algorithms, Detection and tracking algorithms, Data modeling, Sensors, Target detection, Land mines, Electromagnetism, Metals

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Proceedings Article | 7 June 2013 Paper

Detection of shallow buried objects using an autoregressive model on the ground penetrating radar signal

Daniel Nabelek, K. Ho

Proceedings Volume 8709, 87091I (2013) https://doi.org/10.1117/12.2015504

KEYWORDS: Autoregressive models, Target detection, General packet radio service, Detection and tracking algorithms, Data modeling, Sensors, Metals, Ground penetrating radar, Signal detection, Land mines

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Proceedings Article | 7 June 2013 Paper

Landmine classification using possibilistic K-nearest neighbors with wideband electromagnetic induction data

J. Dula, A. Zare, Dominic Ho, P. Gader

Proceedings Volume 8709, 87091F (2013) https://doi.org/10.1117/12.2016490

KEYWORDS: Associative arrays, Land mines, Metals, Detection and tracking algorithms, Electromagnetism, Mining, Sensors, Data modeling, Target detection, Electromagnetic coupling

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Proceedings Article | 18 May 2012 Paper

Multiple kernel learning for explosive hazard detection in forward-looking ground-penetrating radar

Timothy Havens, Kevin Stone, Derek Anderson, James Keller, K. Ho, Tuan Ton, David Wong, Mehrdad Soumekh

Proceedings Volume 8357, 83571D (2012) https://doi.org/10.1117/12.920482

KEYWORDS: Explosives, Image filtering, Explosives detection, Matrices, Imaging systems, Ground penetrating radar, Binary data, Sensors, Detection and tracking algorithms, Infrared cameras

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Proceedings Article | 11 May 2012 Paper

Evaluation and improvement of spectral features for the detection of buried explosive hazards using forward-looking ground-penetrating radar

Justin Farrell, Timothy Havens, K. Ho, James Keller, Tuan Ton, David Wong, Mehrdad Soumekh

Proceedings Volume 8357, 83571C (2012) https://doi.org/10.1117/12.918779

KEYWORDS: Explosives, Metals, Target detection, Explosives detection, Feature extraction, Radar, Image filtering, Ground penetrating radar, Sensors, Signal detection

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Proceedings Article | 11 May 2012 Paper

On the estimation of target depth using the single transmit multiple receive metal detector array

K. Ho, P. Gader

Proceedings Volume 8357, 835709 (2012) https://doi.org/10.1117/12.918778

KEYWORDS: Sensors, Target detection, Metals, Electromagnetic coupling, Detector arrays, General packet radio service, Signal processing, Transmitters, Holmium, Molybdenum

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Proceedings Article | 23 May 2011 Paper

Narrow-band processing and fusion approach for explosive hazard detection in FLGPR

Timothy Havens, James Keller, K. Ho, Tuan Ton, David Wong, Mehrdad Soumekh

Proceedings Volume 8017, 80171F (2011) https://doi.org/10.1117/12.884610

KEYWORDS: Radar, Image filtering, Image fusion, Explosives, Detection and tracking algorithms, Explosives detection, Image processing, Target detection, Imaging systems, Image resolution

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Proceedings Article | 23 May 2011 Paper

Detection of explosive hazards using spectrum features from forward-looking ground penetrating radar imagery

Justin Farrell, Timothy Havens, K. Ho, James Keller, Tuan Ton, David Wong, Mehrdad Soumekh

Proceedings Volume 8017, 80171E (2011) https://doi.org/10.1117/12.884685

KEYWORDS: Explosives, Explosives detection, Radar, Image filtering, Detection and tracking algorithms, Ground penetrating radar, Feature extraction, General packet radio service, Target detection, Data modeling

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