47 citations · 91 across the 11 of their papers we have counts for
13 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…
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…
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…
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…
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…
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…
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…
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…
Information theoretic approach to robust multi-Bernoulli sensor control
Amirali K. Gostar, Reza Hoseinnezhad, Alireza Bab-Hadiashar
A novel sensor control solution is presented, formulated within a Multi-Bernoulli-based multi-target tracking framework. The proposed method is especially designed for the general…
Sensor Control for Multi-Object Tracking Using Labeled Multi-Bernoulli Filter
Amirali K. Gostar, Reza Hoseinnezhad, Alireza Bab-Hadiashar
The recently developed labeled multi-Bernoulli (LMB) filter uses better approximations in its update step, compared to the unlabeled multi-Bernoulli filters, and more importantly,…