47 citations · 117 across the 26 of their papers we have counts for
30 papers
RMR-P: Road Metadata-Aware Restoration for Pavement Inspection
Amir Ghorbani, Amirali K. Gostar, WeiQin Chuah +4
Road-surface images captured by vehicle-mounted cameras are often degraded by motion blur, defocus, poor illumination, and noise due to vehicle motion, camera limitations, and vary…
Distributed Multi-Sensor Control for Multi-Target Tracking Using Adaptive Complementary Fusion for LMB Densities
Aidan Blair, Amirali Khodadadian Gostar, Alireza Bab-Hadiashar +2
Tracking multiple targets in dynamic environments using distributed sensor networks is a fundamental problem in statistical signal processing. In such scenarios, the network of mob…
Automated Keypoint Estimation for Self-Piercing Rivet Joints Using micro-CT Imaging and Transfer Learning
Wei Qin Chuah, Ruwan Tennakoon, Amanda Freis +3
The structural integrity of self-piercing rivet (SPR) joints is critical in automotive industries, yet its evaluation poses challenges due to the limitations of traditional destruc…
Generalization Capabilities of Neural Cellular Automata for Medical Image Segmentation: A Robust and Lightweight Approach
Steven Korevaar, Ruwan Tennakoon, Alireza Bab-Hadiashar
In the field of medical imaging, the U-Net architecture, along with its variants, has established itself as a cornerstone for image segmentation tasks, particularly due to its stro…
Enhanced Online Test-time Adaptation with Feature-Weight Cosine Alignment
WeiQin Chuah, Ruwan Tennakoon, Alireza Bab-Hadiashar
Online Test-Time Adaptation (OTTA) has emerged as an effective strategy to handle distributional shifts, allowing on-the-fly adaptation of pre-trained models to new target domains…
Enhanced Multi-Target Tracking in Dynamic Environments: Distributed Flooding Control in the Random Finite Set Framework
Aidan Blair, Amirali Khodadadian Gostar, Alireza Bab-Hadiashar +2
Tracking multiple targets in dynamic environments using distributed sensor networks is a challenging problem for situational awareness in connected autonomous vehicles (CAVs). In s…
Single Domain Generalization via Normalised Cross-correlation Based Convolutions
WeiQin Chuah, Ruwan Tennakoon, Reza Hoseinnezhad +2
Deep learning techniques often perform poorly in the presence of domain shift, where the test data follows a different distribution than the training data. The most practically des…
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…
Maximum Consensus by Weighted Influences of Monotone Boolean Functions
Erchuan Zhang, David Suter, Ruwan Tennakoon +4
Robust model fitting is a fundamental problem in computer vision: used to pre-process raw data in the presence of outliers. Maximisation of Consensus (MaxCon) is one of the most po…
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…
Robust Pooling through the Data Mode
Ayman Mukhaimar, Ruwan Tennakoon, Chow Yin Lai +2
The task of learning from point cloud data is always challenging due to the often occurrence of noise and outliers in the data. Such data inaccuracies can significantly influence t…
Achieving Domain Robustness in Stereo Matching Networks by Removing Shortcut Learning
WeiQin Chuah, Ruwan Tennakoon, Alireza Bab-Hadiashar +1
Learning-based stereo matching and depth estimation networks currently excel on public benchmarks with impressive results. However, state-of-the-art networks often fail to generali…
Consensus Maximisation Using Influences of Monotone Boolean Functions
Ruwan Tennakoon, David Suter, Erchuan Zhang +2
Consensus maximisation (MaxCon), which is widely used for robust fitting in computer vision, aims to find the largest subset of data that fits the model within some tolerance level…
Evaluation of Point Pattern Features for Anomaly Detection of Defect within Random Finite Set Framework
Ammar Mansoor Kamoona, Amirali Khodadadian Gostar, Alireza Bab-Hadiashar +1
Defect detection in the manufacturing industry is of utmost importance for product quality inspection. Recently, optical defect detection has been investigated as an anomaly detect…
Rotation Averaging with Attention Graph Neural Networks
Joshua Thorpe, Ruwan Tennakoon, Alireza Bab-Hadiashar
In this paper we propose a real-time and robust solution to large-scale multiple rotation averaging. Until recently, Multiple rotation averaging problem had been solved using conve…
Robust Object Classification Approach using Spherical Harmonics
Ayman Mukhaimar, Ruwan Tennakoon, Chow Yin Lai +2
In this paper, we present a robust spherical harmonics approach for the classification of point cloud-based objects. Spherical harmonics have been used for classification over the…
Adjusting Bias in Long Range Stereo Matching: A semantics guided approach
WeiQin Chuah, Ruwan Tennakoon, Reza Hoseinnezhad +2
Stereo vision generally involves the computation of pixel correspondences and estimation of disparities between rectified image pairs. In many applications, including simultaneous…
Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-Decoding
Ammar Mansoor Kamoona, Amirali Khodadadian Gosta, Alireza Bab-Hadiashar +1
In this paper, we propose a weakly supervised deep temporal encoding-decoding solution for anomaly detection in surveillance videos using multiple instance learning. The proposed a…
Monotone Boolean Functions, Feasibility/Infeasibility, LP-type problems and MaxCon
David Suter, Ruwan Tennakoon, Erchuan Zhang +2
This paper outlines connections between Monotone Boolean Functions, LP-Type problems and the Maximum Consensus Problem. The latter refers to a particular type of robust fitting cha…
Effective Sampling: Fast Segmentation Using Robust Geometric Model Fitting
Ruwan Tennakoon, Alireza Sadri, Reza Hoseinnezhad +1
Identifying the underlying models in a set of data points contaminated by noise and outliers, leads to a highly complex multi-model fitting problem. This problem can be posed as a…