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Deep Learning for Robot Perception and Cognition by Alexandros Iosifidis (Aarhus University, Denmark) at Abbey's Bookshop,
Deep Learning for Robot Perception and Cognition
— —
Alexandros Iosifidis (Aarhus University, Denmark) Anastasios Tefas (Department of Informatics, Aristotle University of Thessaloniki)

Deep Learning for Robot Perception and Cognition

Alexandros Iosifidis (Aarhus University, Denmark),  Anastasios Tefas (Department of Informatics, Aristotle University of Thessaloniki),  Anastasios Tefas (Department of Informatics, Aristotle University of Thessaloniki) ,  Anastasios Tefas (Department of Informatics, Aristotle University of Thessaloniki)

$238.95

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English
Academic Press Inc
10 March 2022
Robotics; Machine learning; Neural networks & fuzzy systems
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.
Edited by:   , , , , , ,
Imprint:   Academic Press Inc
Country of Publication:   United Kingdom
Dimensions:   Height: 235mm,  Width: 191mm, 
Weight:   1.310kg
ISBN:   9780323857871
ISBN 10:   0323857876
Pages:   634
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
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

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. Anastasios Tefas received the B.Sc. in Informatics in 1997 and the Ph.D. degree in Informatics in 2002, both from the Aristotle University of Thessaloniki, Greece. Since 2017, he has been an Associate Professor at the Department of Informatics, Aristotle University of Thessaloniki. Dr. Tefas participated in 20 research projects financed by national and European funds. He is the coordinator of the H2020 project OpenDR, “Open Deep Learning Toolkit for Robotics.”

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