Deep Learning for Robot Perception and Cognition

Erscheinungsjahr 2022
ISBN: 978-0-323-85787-1
Verlag: Elsevier Science & Technology

Buch, Englisch, 634 Seiten, Format (B × H): 235 mm x 192 mm, Gewicht: 1298 g

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.

Autoren/Hrsg.

Iosifidis, Alexandros

Tefas, Anastasios

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau Mechatronik, Mikrosysteme (MEMS), Nanosysteme
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision

Inhaltsverzeichnis

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

Über Autor(innen)

Iosifidis, Alexandros
Alexandros Iosifidis is a Professor at Aarhus University, Denmark. He leads the Machine Learning and
Computational Intelligence group at the Department of Electrical and Computer Engineering. He received his Ph.D.
from the Department of Informatics at Aristotle University of Thessaloniki, Greece in 2014. He participated in more
than 15 research and development projects financed by national and European funds.