222 citations · 258 across the 7 of their papers we have counts for
8 papers
AUTOPILOT VQA: Benchmarking Vision-Language Models for Incident-Centric Dashcam Understanding
Siddharth Damodharan, Radhika Gupta, Ali Alshami +2
Recent advances in Vision-Language Models, Large Language Models, and Multimodal Large Language Models have improved autonomous driving tasks such as scene understanding, decision…
Drug Repurposing Using Deep Embedded Clustering and Graph Neural Networks
Luke Delzer, Robert Kroleski, Ali K. AlShami +1
Drug repurposing has historically been an economically infeasible process for identifying novel uses for abandoned drugs. Modern machine learning has enabled the identification of…
2COOOL: 2nd Workshop on the Challenge Of Out-Of-Label Hazards in Autonomous Driving
Ali K. AlShami, Ryan Rabinowitz, Maged Shoman +9
As the computer vision community advances autonomous driving algorithms, integrating vision-based insights with sensor data remains essential for improving perception, decision mak…
SGNetPose+: Stepwise Goal-Driven Networks with Pose Information for Trajectory Prediction in Autonomous Driving
Akshat Ghiya, Ali K. AlShami, Jugal Kalita
Predicting pedestrian trajectories is essential for autonomous driving systems, as it significantly enhances safety and supports informed decision-making. Accurate predictions enab…
SMART-Vision: Survey of Modern Action Recognition Techniques in Vision
Ali K. AlShami, Ryan Rabinowitz, Khang Lam +4
Human Action Recognition (HAR) is a challenging domain in computer vision, involving recognizing complex patterns by analyzing the spatiotemporal dynamics of individuals' movements…
COOOL: Challenge Of Out-Of-Label A Novel Benchmark for Autonomous Driving
Ali K. AlShami, Ananya Kalita, Ryan Rabinowitz +4
As the Computer Vision community rapidly develops and advances algorithms for autonomous driving systems, the goal of safer and more efficient autonomous transportation is becoming…
Pose2Trajectory: Using Transformers on Body Pose to Predict Tennis Player's Trajectory
Ali K. AlShami, Terrance Boult, Jugal Kalita
Tracking the trajectory of tennis players can help camera operators in production. Predicting future movement enables cameras to automatically track and predict a player's future t…
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction
Melkamu Mersha, Khang Lam, Joseph Wood +2
Artificial intelligence models encounter significant challenges due to their black-box nature, particularly in safety-critical domains such as healthcare, finance, and autonomous v…