Deep learning for robot perception and cognition

Author(s)

    • Iosifidis, Alexandros
    • Tefas, Anastasios

Bibliographic Information

Deep learning for robot perception and cognition

edited by Alexandros Iosifidis, Anastasios Tefas

Academic Press, 2022

  • pbk.

Available at  / 3 libraries

Search this Book/Journal

Description and Table of Contents

Description

Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks.

Table of Contents

1. Introduction 2. Neural Networks and Backpropagation 3. Convolutional Neural Networks 4. Graph Convolutional Networks 5. Recurrent Neural Networks 6. Deep Reinforcement Learning 7. Lightweight Deep Learning 8. Knowledge Distillation 9. Progressive and Compressive Deep Learning 10. Representation Learning and Retrieval 11. Object Detection and Tracking 12. Semantic Scene Segmentation for Robotics 13. 3D Object Detection and Tracking 14. Human Activity Recognition 15. Deep Learning for Vision-based Navigation in Autonomous Drone Racing 16. Robotic Grasping in Agile Production 17. Deep learning in Multiagent Systems 18. Simulation Environments 19. Biosignal time-series analysis 20. Medical Image Analysis 21. Deep learning for robotics examples using OpenDR

by "Nielsen BookData"

Details

Page Top