148 citations · 492 across the 23 of their papers we have counts for
26 papers
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…
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…
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…
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…
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…
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…
Computationally Efficient Distributed Multi-sensor Fusion with Multi-Bernoulli Filter
Wei Yi, Suqi Li, Bailu Wang +2
This paper proposes a computationally efficient algorithm for distributed fusion in a sensor network in which multi-Bernoulli (MB) filters are locally running in every sensor node…
Robust Distributed Fusion with Labeled Random Finite Sets
Suqi Li, Wei Yi, Reza Hoseinnezhad +3
This paper considers the problem of the distributed fusion of multi-object posteriors in the labeled random finite set filtering framework, using Generalized Covariance Intersectio…
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…
Statistical Information Fusion for Multiple-View Sensor Data in Multi-Object Tracking
Xiaoying Wang, Reza Hoseinnezhad, Amirali K. Gostar +3
This paper presents a novel statistical information fusion method to integrate multiple-view sensor data in multi-object tracking applications. The proposed method overcomes the dr…
Multi-Sensor Control for Multi-Object Bayes Filters
Xiaoying Wang, Reza Hoseinnezhad, Amirali K. Gostar +3
Sensor management in multi-object stochastic systems is a theoretically and computationally challenging problem. This paper presents a novel approach to the multi-target multi-sens…
Labeled Multi-Bernoulli Tracking for Industrial Mobile Platform Safety
Tharindu Rathnayake, Reza Hoseinnezhad, Ruwan Tennakoon +1
This paper presents a track-before-detect labeled multi-Bernoulli filter tailored for industrial mobile platform safety applications. We derive two application specific separable l…
Multi-object Tracking for Generic Observation Model Using Labeled Random Finite Sets
Suqi Li, Wei Yi, Reza Hoseinnezhad +2
This paper presents an exact Bayesian filtering solution for the multi-object tracking problem with the generic observation model. The proposed solution is designed in the labeled…
Distributed Multi-Sensor Fusion Using Generalized Multi-Bernoulli Densities
Meng Jiang, Wei Yi, Reza Hoseinnezhad +1
The paper addresses distributed multi-target tracking in the framework of generalized Covariance Intersection (GCI) over multistatic radar system. The proposed method is based on t…
Distributed Fusion with Multi-Bernoulli Filter based on Generalized Covariance Intersection
Bailu Wang, Wei Yi, Reza Hoseinnezhad +3
In this paper, we propose a distributed multi-object tracking algorithm through the use of multi-Bernoulli (MB) filter based on generalized Covariance Intersection (G-CI). Our anal…
Multi-Bernoulli Sensor-Control via Minimization of Expected Estimation Errors
Amirali K. Gostar, Reza Hoseinnezhad, Alireza Bab-Hadiashar
This paper presents a sensor-control method for choosing the best next state of the sensor(s), that provide(s) accurate estimation results in a multi-target tracking application. T…