3 citations · 3 across the 9 of their papers we have counts for
15 papers
IT-RUDA: Information Theory Assisted Robust Unsupervised Domain Adaptation
Shima Rashidi, Ruwan Tennakoon, Aref Miri Rekavandi +7
Distribution shift between train (source) and test (target) datasets is a common problem encountered in machine learning applications. One approach to resolve this issue is to use…
Distributed Complementary Fusion for Connected Vehicles
James Klupacs, Amirali Khodadadian Gostar, Alireza Bab-Hadiashar +2
We present a random finite set-based method for achieving comprehensive situation awareness by each vehicle in a distributed vehicle network. Our solution is designed for labeled m…
Interaction-Aware Labeled Multi-Bernoulli Filter
Nida Ishtiaq, Amirali Khodadadian Gostar, Alireza Bab-Hadiashar +1
Tracking multiple objects through time is an important part of an intelligent transportation system. Random finite set (RFS)-based filters are one of the emerging techniques for tr…
ITSA: An Information-Theoretic Approach to Automatic Shortcut Avoidance and Domain Generalization in Stereo Matching Networks
WeiQin Chuah, Ruwan Tennakoon, Reza Hoseinnezhad +2
State-of-the-art stereo matching networks trained only on synthetic data often fail to generalize to more challenging real data domains. In this paper, we attempt to unfold an impo…
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework
Ammar Mansoor Kamoona, Amirali Khodadadian Gostar, Alireza Bab-Hadiashar +1
In this paper, we propose an efficient approach for industrial defect detection that is modeled based on anomaly detection using point pattern data. Most recent works use \textit{g…
Cable Driven Rehabilitation Robots: Comparison of Applications and Control Strategies
Muhammad Shoaib, Ehsan Asadi, Joono Cheong +1
Significant attention has been paid to robotic rehabilitation using various types of actuator and power transmission. Amongst those, cable-driven rehabilitation robots (CDRRs) are…