145 citations · 216 across the 12 of their papers we have counts for
12 papers
LSTM-based Preceding Vehicle Behaviour Prediction during Aggressive Lane Change for ACC Application
Rajmeet Singh, Saeed Mozaffari, Mahdi Rezaei +1
The development of Adaptive Cruise Control (ACC) systems aims to enhance the safety and comfort of vehicles by automatically regulating the speed of the vehicle to ensure a safe ga…
Local and Global Contextual Features Fusion for Pedestrian Intention Prediction
Mohsen Azarmi, Mahdi Rezaei, Tanveer Hussain +1
Autonomous vehicles (AVs) are becoming an indispensable part of future transportation. However, safety challenges and lack of reliability limit their real-world deployment. Towards…
A Novel Model for Driver Lane Change Prediction in Cooperative Adaptive Cruise Control Systems
Armin Nejadhossein Qasemabadi, Saeed Mozaffari, Mahdi Rezaei +2
Accurate lane change prediction can reduce potential accidents and contribute to higher road safety. Adaptive cruise control (ACC), lane departure avoidance (LDA), and lane keeping…
Multi-level and multi-modal feature fusion for accurate 3D object detection in Connected and Automated Vehicles
Yiming Hou, Mahdi Rezaei, Richard Romano
Aiming at highly accurate object detection for connected and automated vehicles (CAVs), this paper presents a Deep Neural Network based 3D object detection model that leverages a t…
Traffic-Net: 3D Traffic Monitoring Using a Single Camera
Mahdi Rezaei, Mohsen Azarmi, Farzam Mohammad Pour Mir
Computer Vision has played a major role in Intelligent Transportation Systems (ITS) and traffic surveillance. Along with the rapidly growing automated vehicles and crowded cities,…
Curious Exploration and Return-based Memory Restoration for Deep Reinforcement Learning
Saeed Tafazzol, Erfan Fathi, Mahdi Rezaei +1
Reward engineering and designing an incentive reward function are non-trivial tasks to train agents in complex environments. Furthermore, an inaccurate reward function may lead to…
Real-time Active Vision for a Humanoid Soccer Robot Using Deep Reinforcement Learning
Soheil Khatibi, Meisam Teimouri, Mahdi Rezaei
In this paper, we present an active vision method using a deep reinforcement learning approach for a humanoid soccer-playing robot. The proposed method adaptively optimises the vie…
DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic
Mahdi Rezaei, Mohsen Azarmi
Social distancing is a recommended solution by the World Health Organisation (WHO) to minimise the spread of COVID-19 in public places. The majority of governments and national hea…
DeepHAZMAT: Hazardous Materials Sign Detection and Segmentation with Restricted Computational Resources
Amir Sharifi, Ahmadreza Zibaei, Mahdi Rezaei
One of the most challenging and non-trivial tasks in robot-based rescue operations is the Hazardous Materials or HAZMATs sign detection in the operation field, to prevent further u…
Complex Human Action Recognition in Live Videos Using Hybrid FR-DL Method
Fatemeh Serpush, Mahdi Rezaei
Automated human action recognition is one of the most attractive and practical research fields in computer vision, in spite of its high computational costs. In such systems, the hu…
Deep-CAPTCHA: a deep learning based CAPTCHA solver for vulnerability assessment
Zahra Noury, Mahdi Rezaei
CAPTCHA is a human-centred test to distinguish a human operator from bots, attacking programs, or other computerised agents that tries to imitate human intelligence. In this resear…
Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review
Mahdi Rezaei, Mahsa Shahidi
The challenge of learning a new concept, object, or a new medical disease recognition without receiving any examples beforehand is called Zero-Shot Learning (ZSL). One of the major…