5 citations · 5 across the 7 of their papers we have counts for
7 papers
Evaluating the Effectiveness of Video Anomaly Detection in the Wild: Online Learning and Inference for Real-world Deployment
Shanle Yao, Ghazal Alinezhad Noghre, Armin Danesh Pazho +1
Video Anomaly Detection (VAD) identifies unusual activities in video streams, a key technology with broad applications ranging from surveillance to healthcare. Tackling VAD in real…
VegaEdge: Edge AI Confluence Anomaly Detection for Real-Time Highway IoT-Applications
Vinit Katariya, Fatema-E- Jannat, Armin Danesh Pazho +2
Vehicle anomaly detection plays a vital role in highway safety applications such as accident prevention, rapid response, traffic flow optimization, and work zone safety. With the s…
Real-Time Online Unsupervised Domain Adaptation for Real-World Person Re-identification
Christopher Neff, Armin Danesh Pazho, Hamed Tabkhi
Following the popularity of Unsupervised Domain Adaptation (UDA) in person re-identification, the recently proposed setting of Online Unsupervised Domain Adaptation (OUDA) attempts…
Real-World Community-in-the-Loop Smart Video Surveillance -- A Case Study at a Community College
Shanle Yao, Babak Rahimi Ardabili, Armin Danesh Pazho +3
Smart Video surveillance systems have become important recently for ensuring public safety and security, especially in smart cities. However, applying real-time artificial intellig…
A POV-based Highway Vehicle Trajectory Dataset and Prediction Architecture
Vinit Katariya, Ghazal Alinezhad Noghre, Armin Danesh Pazho +1
Vehicle Trajectory datasets that provide multiple point-of-views (POVs) can be valuable for various traffic safety and management applications. Despite the abundance of trajectory…
Understanding the Challenges and Opportunities of Pose-based Anomaly Detection
Ghazal Alinezhad Noghre, Armin Danesh Pazho, Vinit Katariya +1
Pose-based anomaly detection is a video-analysis technique for detecting anomalous events or behaviors by examining human pose extracted from the video frames. Utilizing pose data…