Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Azarmi, Mohsen"'
Recent advancements in predicting pedestrian crossing intentions for Autonomous Vehicles using Computer Vision and Deep Neural Networks are promising. However, the black-box nature of DNNs poses challenges in understanding how the model works and how
Externí odkaz:
http://arxiv.org/abs/2409.07645
Autor:
Qian, Chenghao, Rezaei, Mahdi, Anwar, Saeed, Li, Wenjing, Hussain, Tanveer, Azarmi, Mohsen, Wang, Wei
Adverse conditions like snow, rain, nighttime, and fog, pose challenges for autonomous driving perception systems. Existing methods have limited effectiveness in improving essential computer vision tasks, such as semantic segmentation, and often focu
Externí odkaz:
http://arxiv.org/abs/2409.02045
Accurate pedestrian intention prediction (PIP) by Autonomous Vehicles (AVs) is one of the current research challenges in this field. In this article, we introduce PIP-Net, a novel framework designed to predict pedestrian crossing intentions by AVs in
Externí odkaz:
http://arxiv.org/abs/2402.12810
Evaluating Driver Readiness in Conditionally Automated Vehicles from Eye-Tracking Data and Head Pose
As automated driving technology advances, the role of the driver to resume control of the vehicle in conditionally automated vehicles becomes increasingly critical. In the SAE Level 3 or partly automated vehicles, the driver needs to be available and
Externí odkaz:
http://arxiv.org/abs/2401.11284
Autonomous vehicles (AVs) are becoming an indispensable part of future transportation. However, safety challenges and lack of reliability limit their real-world deployment. Towards boosting the appearance of AVs on the roads, the interaction of AVs w
Externí odkaz:
http://arxiv.org/abs/2305.01111
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, the automated and advanced traffic management systems (ATMS) using vid
Externí odkaz:
http://arxiv.org/abs/2109.09165
Autor:
Rezaei, Mahdi, Azarmi, Mohsen
Publikováno v:
Applied Sciences. 2020, 10, 7514
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 health authorities have set the 2-meter physical distancing as a mandator
Externí odkaz:
http://arxiv.org/abs/2008.11672
Publikováno v:
In Expert Systems With Applications 1 October 2023 227
