3D Scene Reconstruction through a Fusion of Passive Video and Lidar Imagery. - Prudhvi Gurram; Stephen R. Lach; Eli Saber; Harvey E. Rhody; John P. Kerekes (AIPR, 2007)

Automated 3D object identification using Bayesian networks. - Prudhvi Gurram; Eli Saber; Ferat Sahin; Harvey E. Rhody (AIPR, 2009)

A full diagonal bandwidth gaussian kernel SVM based ensemble learning for hyperspectral chemical plume detection. - Prudhvi Gurram; Heesung Kwon (IGARSS, 2010)

Optimal kernel bandwidth estimation for hyperspectral kernel-based anomaly detection. - Heesung Kwon; Prudhvi Gurram (IGARSS, 2010)

A Segment-Based Mesh Design for Building Parallel-Perspective Stereo Mosaics. - Prudhvi Gurram; Eli Saber; Harvey E. Rhody (IEEE Trans. Geosci. Remote. Sens., 2010)

Generalized optimal Kernel-Based Ensemble Learning for hyperspectral classification problems. - Prudhvi Gurram; Heesung Kwon (IGARSS, 2011)

Hyperspectral anomaly detection using an optimized support vector data description method. - Prudhvi Gurram; Heesung Kwon (WHISPERS, 2011)

Support-Vector-Based Hyperspectral Anomaly Detection Using Optimized Kernel Parameters. - Prudhvi Gurram; Heesung Kwon (IEEE Geosci. Remote. Sens. Lett., 2011)

Contextual SVM for hyperspectral classification using Hilbert Space Embedding. - Prudhvi Gurram; Heesung Kwon (IGARSS, 2012)

Semiautomated system for three-dimensional modeling of buildings from aerial video. - Prudhvi Gurram; Eli Saber; Harvey E. Rhody (J. Electronic Imaging, 2012)

Sparse Kernel-Based Hyperspectral Anomaly Detection. - Prudhvi Gurram; Heesung Kwon; Timothy Han (IEEE Geosci. Remote. Sens. Lett., 2012)

Uniform grid upsampling of 3D lidar point cloud data. - Prudhvi Gurram; Shuowen Hu; Alex L. Chan (Three-Dimensional Image Processing (3DIP) and Applications, 2013)

Optimal sparse kernel learning for hyperspectral anomaly detection. - Prudhvi Gurram; Heesung Kwon; Zhimin Peng; Wotao Yin (WHISPERS, 2013)

Algorithms for Multispectral and Hyperspectral Image Analysis. - Heesung Kwon; Xiaofei Hu; James Theiler; Alina Zare; Prudhvi Gurram (J. Electr. Comput. Eng., 2013)

Contextual SVM Using Hilbert Space Embedding for Hyperspectral Classification. - Prudhvi Gurram; Heesung Kwon (IEEE Geosci. Remote. Sens. Lett., 2013)

Sparse Kernel-Based Ensemble Learning With Fully Optimized Kernel Parameters for Hyperspectral Classification Problems. - Prudhvi Gurram; Heesung Kwon (IEEE Trans. Geosci. Remote. Sens., 2013)

Entropy metric regularization for computational imaging with sensor arrays. - Prudhvi Gurram; Raghuveer M. Rao (AIPR, 2014)

Coalition game theory based feature subset selection for hyperspectral image classification. - Prudhvi Gurram; Heesung Kwon (IGARSS, 2014)

Optimal Sparse Kernel Learning in the Empirical Kernel Feature Space for Hyperspectral Classification. - Prudhvi Gurram; Heesung Kwon (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014)

Exploiting polarization-state information for cross-spectrum face recognition. - Nathaniel J. Short; Shuowen Hu; Prudhvi Gurram; Kristan P. Gurton (BTAS, 2015)

Hierarchical Union-of-Subspaces Model for Human Activity Summarization. - Tong Wu 008; Prudhvi Gurram; Raghuveer M. Rao; Waheed U. Bajwa (ICCV Workshops, 2015)

Shapely value based random subspace selection for hyperspectral image classification. - Prudhvi Gurram; Heesung Kwon; Charles Davidson (IGARSS, 2015)

Sparse kernel learning-based feature selection for anomaly detection. - Zhimin Peng; Prudhvi Gurram; Heesung Kwon; Wotao Yin (IEEE Trans. Aerosp. Electron. Syst., 2015)

MWIR-to-Visible and LWIR-to-Visible Face Recognition Using Partial Least Squares and Dictionary Learning. - Shuowen Hu; Nathaniel J. Short; Prudhvi K. Gurram; Kristan P. Gurton; Christopher Reale (Face Recognition Across the Imaging Spectrum, 2016)

A Polarimetric Thermal Database for Face Recognition Research. - Shuowen Hu; Nathaniel J. Short; Benjamin S. Riggan; Christopher Gordon; Kristan P. Gurton; Matthew Thielke; Prudhvi Gurram; Alex L. Chan (CVPR Workshops, 2016)

Clustering-aware structure-constrained low-rank representation model for learning human action attributes. - Tong Wu 008; Prudhvi Gurram; Raghuveer M. Rao; Waheed U. Bajwa (IVMSP, 2016)

Human Action Attribute Learning From Video Data Using Low-Rank Representations. - Tong Wu 008; Prudhvi Gurram; Raghuveer M. Rao; Waheed U. Bajwa (CoRR, 2016)

Coalition Game Theory-Based Feature Subspace Selection for Hyperspectral Classification. - Prudhvi Gurram; Heesung Kwon; Charles Davidson (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016)

Interpretability of deep learning models: A survey of results. - Supriyo Chakraborty; Richard Tomsett; Ramya Raghavendra; Daniel Harborne; Moustafa Alzantot; Federico Cerutti 001; Mani B. Srivastava; Alun D. Preece; Simon Julier; Raghuveer M. Rao; Troy D. Kelley; Dave Braines; et al. (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI, 2017)

Sequential Event Detection Using Multimodal Data in Nonstationary Environments. - Taposh Banerjee; Gene T. Whipps; Prudhvi Gurram; Vahid Tarokh (FUSION, 2018)

Why the Failure? How Adversarial Examples Can Provide Insights for Interpretable Machine Learning. - Richard Tomsett; Amy Widdicombe; Tianwei Xing; Supriyo Chakraborty; Simon Julier; Prudhvi Gurram; Raghuveer M. Rao; Mani B. Srivastava (FUSION, 2018)

Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data. - Taposh Banerjee; Gene T. Whipps; Prudhvi Gurram; Vahid Tarokh (GlobalSIP, 2018)

A Sequential Detection Theory for Statistically Periodic Random Processes. - Taposh Banerjee; Prudhvi Gurram; Gene T. Whipps (Allerton, 2019)

Distributed Stochastic Gradient Method for Non-Convex Problems with Applications in Supervised Learning. - Jemin George; Tao Yang 003; He Bai 001; Prudhvi Gurram (CDC, 2019)

Quickest Detection of Deviations from Periodic Statistical Behavior. - Taposh Banerjee; Prudhvi Gurram; Gene T. Whipps (ICASSP, 2019)

Bayesian Quickest Detection of Changes in Statistically Periodic Processes. - Taposh Banerjee; Prudhvi Gurram; Gene T. Whipps (ISIT, 2019)

Quickest Event Detection Using Multimodal Data In Nonstationary Environments. - Taposh Banerjee; Prudhvi Gurram; Gene T. Whipps (CoRR, 2019)

Distributed Deep Learning with Event-Triggered Communication. - Jemin George; Prudhvi Gurram (CoRR, 2019)

Wasserstein Distance Based Domain Adaptation for Object Detection. - Pengcheng Xu; Prudhvi Gurram; Gene T. Whipps; Rama Chellappa (CoRR, 2019)

Distributed Stochastic Gradient Descent with Event-Triggered Communication. - Jemin George; Prudhvi Gurram (AAAI, 2020)

Sanity Checks for Saliency Metrics. - Richard Tomsett; Dan Harborne; Supriyo Chakraborty; Prudhvi Gurram; Alun D. Preece (AAAI, 2020)

Vision-Based Gesture Recognition in Human-Robot Teams Using Synthetic Data. - Celso M. de Melo; Brandon Rothrock; Prudhvi Gurram; Oytun Ulutan; B. S. Manjunath (IROS, 2020)

Multislot and Multistream Quickest Change Detection in Statistically Periodic Processes. - Taposh Banerjee; Prudhvi Gurram; Gene T. Whipps (ISIT, 2020)

Decentralized Langevin Dynamics for Bayesian Learning. - Anjaly Parayil; He Bai 001; Jemin George; Prudhvi Gurram (NeurIPS, 2020)

Explaining Motion Relevance for Activity Recognition in Video Deep Learning Models. - Liam Hiley; Alun D. Preece; Yulia Hicks; Supriyo Chakraborty; Prudhvi Gurram; Richard Tomsett (CoRR, 2020)

A Decentralized Approach to Bayesian Learning. - Anjaly Parayil; He Bai 001; Jemin George; Prudhvi Gurram (CoRR, 2020)

A Bayesian Theory of Change Detection in Statistically Periodic Random Processes. - Taposh Banerjee; Prudhvi Gurram; Gene T. Whipps (IEEE Trans. Inf. Theory, 2021)

Minimax asymptotically optimal quickest change detection for statistically periodic data. - Taposh Banerjee; Prudhvi Gurram; Gene T. Whipps (Signal Process., 2024)