30 citations · 41 across the 19 of their papers we have counts for
4 papers · 1 filter
Uncertainty-Aware Out-of-Distribution Detection with Gaussian Processes
Yang Chen, Chih-Li Sung, Arpan Kusari +2
Deep neural networks (DNNs) are often constructed under the closed-world assumption, which may fail to generalize to the out-of-distribution (OOD) data. This leads to DNNs producin…
Quantifying Context Bias in Domain Adaptation for Object Detection
Hojun Son, Asma Almutairi, Arpan Kusari
Domain adaptation for object detection (DAOD) has become essential to counter performance degradation caused by distribution shifts between training and deployment domains. However…
Fractured Glass, Failing Cameras: Simulating Physics-Based Adversarial Samples for Autonomous Driving Systems
Manav Prabhakar, Jwalandhar Girnar, Arpan Kusari
While much research has recently focused on generating physics-based adversarial samples, a critical yet often overlooked category originates from physical failures within on-board…
Demystifying the Physics of Deep Reinforcement Learning-Based Autonomous Vehicle Decision-Making
Hanxi Wan, Pei Li, Arpan Kusari
With the advent of universal function approximators in the domain of reinforcement learning, the number of practical applications leveraging deep reinforcement learning (DRL) has e…