3 citations · 3 across the 1 of their papers we have counts for
6 papers
Wasserstein Distance Based Domain Adaptation for Object Detection
Pengcheng Xu, Prudhvi Gurram, Gene Whipps +1
In this paper, we present an adversarial unsupervised domain adaptation framework for object detection. Prior approaches utilize adversarial training based on cross entropy between…
A Bayesian Theory of Change Detection in Statistically Periodic Random Processes
Taposh Banerjee, Prudhvi Gurram, Gene Whipps
A new class of stochastic processes called independent and periodically identically distributed (i.p.i.d.) processes is defined to capture periodically varying statistical behavior…
Minimax-Optimal Algorithms for Detecting Changes in Statistically Periodic Random Processes
Taposh Banerjee, Prudhvi Gurram, Gene Whipps
Theory and algorithms are developed for detecting changes in the distribution of statistically periodic random processes. The statistical periodicity is modeled using independent a…
Quickest Detection Of Deviations From Periodic Statistical Behavior
Taposh Banerjee, Prudhvi Gurram, Gene Whipps
A new class of stochastic processes called independent and periodically identically distributed (i.p.i.d.) processes is defined to capture periodically varying statistical behavior…
Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data
Taposh Banerjee, Gene Whipps, Prudhvi Gurram +1
A framework is proposed to detect anomalies in multi-modal data. A deep neural network-based object detector is employed to extract counts of objects and sub-events from the data.…
Sequential Event Detection Using Multimodal Data in Nonstationary Environments
Taposh Banerjee, Gene Whipps, Prudhvi Gurram +1
The problem of sequential detection of anomalies in multimodal data is considered. The objective is to observe physical sensor data from CCTV cameras, and social media data from Tw…