[HTML][HTML] Deep learning for object detection and scene perception in self-driving cars: Survey, challenges, and open issues
This article presents a comprehensive survey of deep learning applications for object
detection and scene perception in autonomous vehicles. Unlike existing review papers, we …
detection and scene perception in autonomous vehicles. Unlike existing review papers, we …
Deep learning for change detection in remote sensing images: Comprehensive review and meta-analysis
L Khelifi, M Mignotte - Ieee Access, 2020 - ieeexplore.ieee.org
Deep learning (DL) algorithms are considered as a methodology of choice for remote-
sensing image analysis over the past few years. Due to its effective applications, deep …
sensing image analysis over the past few years. Due to its effective applications, deep …
Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness
Driving safety is the most important element that needs to be considered for autonomous
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
Deep reinforcement learning for intelligent transportation systems: A survey
Latest technological improvements increased the quality of transportation. New data-driven
approaches bring out a new research direction for all control-based systems, eg, in …
approaches bring out a new research direction for all control-based systems, eg, in …
Web3-based decentralized autonomous organizations and operations: Architectures, models, and mechanisms
Empowered by blockchain and Web3 technologies, decentralized autonomous
organizations (DAOs) are able to redefine resources, production relations, and …
organizations (DAOs) are able to redefine resources, production relations, and …
Beverse: Unified perception and prediction in birds-eye-view for vision-centric autonomous driving
In this paper, we present BEVerse, a unified framework for 3D perception and prediction
based on multi-camera systems. Unlike existing studies focusing on the improvement of …
based on multi-camera systems. Unlike existing studies focusing on the improvement of …
Survey of deep reinforcement learning for motion planning of autonomous vehicles
S Aradi - IEEE Transactions on Intelligent Transportation …, 2020 - ieeexplore.ieee.org
Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …
recent years related to several topics as sensor technologies, V2X communications, safety …
Robust lane change decision making for autonomous vehicles: An observation adversarial reinforcement learning approach
Reinforcementlearning holds the promise of allowing autonomous vehicles to learn complex
decision making behaviors through interacting with other traffic participants. However, many …
decision making behaviors through interacting with other traffic participants. However, many …
Risk assessment based collision avoidance decision-making for autonomous vehicles in multi-scenarios
In this paper, we proposed a new risk assessment based decision-making algorithm to
guarantee collision avoidance in multi-scenarios for autonomous vehicles. A probabilistic …
guarantee collision avoidance in multi-scenarios for autonomous vehicles. A probabilistic …
Path planning based on deep reinforcement learning for autonomous underwater vehicles under ocean current disturbance
The path planning issue of the underactuated autonomous underwater vehicle (AUV) under
ocean current disturbance is studied in this paper. In order to improve the AUV's path …
ocean current disturbance is studied in this paper. In order to improve the AUV's path …