69 citations · 78 across the 12 of their papers we have counts for
14 papers
Intelligent CCTV for Urban Design: AI-Based Analysis of Soft Infrastructure at Intersections
Vinit Katariya, Seungjin Kim, Curtis Craig +2
Artificial intelligence (AI) and computer vision are transforming transportation data collection. This study introduces an AI-enabled analytics framework leveraging existing CCTV i…
EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applications
Seungjin Kim, Reza Jafarpourmarzouni, Christopher Neff +2
Vehicle trajectory prediction is central to highway perception, but deployment on roadside edge devices necessitates bounded, deterministic end-to-end latency. We present EdgeVTP,…
Distributed learning for automatic modulation recognition in bandwidth-limited networks
Narges Rashvand, Kenneth Witham, Gabriel Maldonado +4
Automatic Modulation Recognition (AMR) is critical in identifying various modulation types in wireless communication systems. Recent advancements in deep learning have facilitated…
Adversarially-Refined VQ-GAN with Dense Motion Tokenization for Spatio-Temporal Heatmaps
Gabriel Maldonado, Narges Rashvand, Armin Danesh Pazho +3
Continuous human motion understanding remains a core challenge in computer vision due to its high dimensionality and inherent redundancy. Efficient compression and representation a…
MoCLIP: Motion-Aware Fine-Tuning and Distillation of CLIP for Human Motion Generation
Gabriel Maldonado, Armin Danesh Pazho, Ghazal Alinezhad Noghre +2
Human motion generation is essential for fields such as animation, robotics, and virtual reality, requiring models that effectively capture motion dynamics from text descriptions.…
Towards Adaptive Human-centric Video Anomaly Detection: A Comprehensive Framework and A New Benchmark
Armin Danesh Pazho, Shanle Yao, Ghazal Alinezhad Noghre +3
Human-centric Video Anomaly Detection (VAD) aims to identify human behaviors that deviate from normal. At its core, human-centric VAD faces substantial challenges, such as the comp…
Enhancing Automatic Modulation Recognition for IoT Applications Using Transformers
Narges Rashvand, Kenneth Witham, Gabriel Maldonado +4
Automatic modulation recognition (AMR) is vital for accurately identifying modulation types within incoming signals, a critical task for optimizing operations within edge devices i…
Exploring Public's Perception of Safety and Video Surveillance Technology: A Survey Approach
Babak Rahimi Ardabili, Armin Danesh Pazho, Ghazal Alinezhad Noghre +4
Addressing public safety effectively requires incorporating diverse stakeholder perspectives, particularly those of the community, which are often underrepresented compared to othe…
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…
VT-Former: An Exploratory Study on Vehicle Trajectory Prediction for Highway Surveillance through Graph Isomorphism and Transformer
Armin Danesh Pazho, Ghazal Alinezhad Noghre, Vinit Katariya +1
Enhancing roadway safety has become an essential computer vision focus area for Intelligent Transportation Systems (ITS). As a part of ITS, Vehicle Trajectory Prediction (VTP) aims…
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…
Pishgu: Universal Path Prediction Network Architecture for Real-time Cyber-physical Edge Systems
Ghazal Alinezhad Noghre, Vinit Katariya, Armin Danesh Pazho +2
Path prediction is an essential task for many real-world Cyber-Physical Systems (CPS) applications, from autonomous driving and traffic monitoring/management to pedestrian/worker s…
DeepTrack: Lightweight Deep Learning for Vehicle Path Prediction in Highways
Vinit Katariya, Mohammadreza Baharani, Nichole Morris +2
Vehicle trajectory prediction is essential for enabling safety-critical intelligent transportation systems (ITS) applications used in management and operations. While there have be…