This book captures multidisciplinary research encompassing various facets of autonomous vehicles systems research and developments.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Ishwar K. Sethi is currently a professor in the Department of Computer Science and Engineering at Oakland University in Rochester, Michigan. He has over 45 years of experience in applying neural networks including deep learning, machine learning, pattern recognition, and image, video, and text analytics to a broad range of projects. He has authored or coauthored over 175 journal and conference articles and has graduated 25 doctoral students. He has served on the editorial boards of several prominent journals including IEEE Trans. Pattern Analysis and Machine Intelligence, and IEEE Multimedia. He was elected IEEE Fellow in 2001 for his contributions in artificial neural networks and statistical pattern recognition and achieved the status of Life Fellow in 2012. He most recently organized the 20th International Conference on Machine Learning and Applications (ICMLA) in December 2021.
Inhaltsangabe
1. Introduction 2. Deep Learning for Autonomous Vehicles and Systems 3. Towards Autonomous Vehicles and Systems - Potentials and Challenges of Artificial Intelligence 4. Autonomous Vehicle Steering through Convolutional and Recurrent Deep Learning 5. 2D and 3D Pose Estimation for Gesture Recognition in Deep-Learning-Driven Human-Vehicle Leader-Follower Systems 6. Adversarial Attacks and Defenses on Autonomous Vehicle Systems 7. Multi-sensor Fusion for Multi-target Detection and Tracking 8. Teleoperation Technologies for Enhancing Connected and Autonomous Vehicles 9. Hybrid Edge/cloud Solutions for Supporting Autonomous Vehicles 10. Game-Theoretic Decision Making for Autonomous Driving Vehicles 11. State of Modeling and Simulation in Autonomous Vehicles 12. Path Following Control System Design and Analysis for Autonomous Vehicles 13. Public Transport Travel Time Prediction using Sequential Forward Floating Selection Algorithm and Stacked Autoencoder 14. A Look into the Ethics of Autonomous Vehicles Systems (AVS)
1. Introduction 2. Deep Learning for Autonomous Vehicles and Systems 3. Towards Autonomous Vehicles and Systems - Potentials and Challenges of Artificial Intelligence 4. Autonomous Vehicle Steering through Convolutional and Recurrent Deep Learning 5. 2D and 3D Pose Estimation for Gesture Recognition in Deep-Learning-Driven Human-Vehicle Leader-Follower Systems 6. Adversarial Attacks and Defenses on Autonomous Vehicle Systems 7. Multi-sensor Fusion for Multi-target Detection and Tracking 8. Teleoperation Technologies for Enhancing Connected and Autonomous Vehicles 9. Hybrid Edge/cloud Solutions for Supporting Autonomous Vehicles 10. Game-Theoretic Decision Making for Autonomous Driving Vehicles 11. State of Modeling and Simulation in Autonomous Vehicles 12. Path Following Control System Design and Analysis for Autonomous Vehicles 13. Public Transport Travel Time Prediction using Sequential Forward Floating Selection Algorithm and Stacked Autoencoder 14. A Look into the Ethics of Autonomous Vehicles Systems (AVS)
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