Deep learning for unmanned systems

Deep learning for unmanned systems / Anis Koubaa, Ahmad Taher Azar, editors.

This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not l...

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Bibliographic Details
Other Authors: Koubâa, Anis (Editor), Azar, Ahmad Taher (Editor)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, 2021.
Series:Studies in computational intelligence ; v. 984.
Subjects:
Automated vehicles > Control.
Automated vehicles > Data processing.
Machine learning.
Machine learning
Vehicles.
Aprenentatge automàtic.
Electronic books.
Llibres electrònics.
Online Access:Click for online access
Table of Contents:
  • Deep Learning for Unmanned Autonomous Vehicles: A Comprehensive Review
  • Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment
  • Reactive Obstacle Avoidance Method for a UAV
  • Guaranteed Performances for Learning-Based Control Systems using Robust Control Theory
  • A cascaded deep Neural Network for Position Estimation of Industrial Robots
  • Managing Deep Learning Uncertainty for Autonomous Systems
  • Uncertainty-Aware Autonomous Mobile Robot Navigation with Deep Reinforcement Learning
  • Deep Reinforcement Learning for Autonomous Mobile Networks in Micro-Grids
  • Reinforcement learning for Autonomous Morphing Control and Cooperative Operations of UAV Cluster
  • Image-Based Identification of Animal Breeds Using Deep Learning.

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