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Machine Learning for Robotics Applications, 1st ed. 2021 Studies in Computational Intelligence Series, Vol. 960

Langue : Anglais

Coordonnateurs : Bianchini Monica, Simic Milan, Ghosh Ankush, Shaw Rabindra Nath

Couverture de l’ouvrage Machine Learning for Robotics Applications
Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas ofapplications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book.
Chapter 1.Manipulation of Standard Link Mechanism for Robotic Application using Artificial Neural Network and PID.- Chapter 2. Machine learning-enabled Human Activity Recognition System for Humanoid robot.- Chapter 3. Hospital Assistance Robots-Control Strategy and Machine Learning Technology.- Chapter 4. Cyber Physical System Fraud Analysis by Mobile Robot .- Chapter 5. Design and Development of an Intelligent Robot for Improving Crop Productivity using Machine Learning.- Chapter 6. Integration of Wireless Sensor Network in Robotics.- Chapter 7. Industry 4.0 and Robotics Automation-New Trends in Cyber Security.- Chapter 8. Digital Transformation in Smart Manufacturing with Industrial Robot through Predictive Data Analysis.- Chapter 9. Surveillance Robot in Cyber Intelligence for Vulnerability Detection.- Chapter 10. Framework and Smart Contract for Blockchain Enabled Certificate verification Sys-tem using Robotics.

Monica Bianchini received the Laurea degree cum laude in Applied Mathematics in 1989 and the Ph.D. degree in Computer Science and Control Systems in 1995 from the University of Florence. She is currently an Associate Professor at the Department of Information Engineering and Mathematics of the University of Siena. Her main research interests are in the field of machine learning, with emphasis on neural networks for structured data and deep learning, approximation theory, bioinformatics, and image processing. M. Bianchini has authored more than one hundred papers and has been the editor of books and special issues on international journals in her research field. She has been involved in the organization of several scientific events, including the NATO Advanced Workshop on Limitations and Future Trends in Neural Computation (2001), the 8th AI*IA Conference (2002), GIRPR 2012, the 25th International
Symposium on LogicBasedProgram Synthesis and Transformation, and the ACM International Conference on Computing Frontiers 2017. Prof. Bianchini served/serves as an Associate Editor for IEEE Transactions on Neural Networks (2003-09), Neurocomputing (from 2003), and Int. J. of Computers in Healthcare (from 2010). She is a permanent member of the Editorial Board of IJCNN, ICANN, ICPR, ICPRAM, ESANN, ANNPR and KES.

 

Milan Simic is a Senior Lecturer at RMIT University, School of Engineering, Melbourne, Australia and Visiting Professor at The University Nikola Tesla, Belgrade, Serbia. He is also an Associate Director for the Australia-India Research Centre for Automation Software Engineering (AIRCAUSE). AICAUSE is a joint initiative of RMIT University, State Government of Victoria and ABB Group (India and Australia). He completed his B.E., M.E. and Ph.D. from RMIT University Melbourne, Australia. He has published over 125 peer-reviewed publications, with 493 citations in
Provides future vision on the unexplored areas of applications of robotics using machine learning Presents original research results contributed by active researchers and experts Offers a reference guide for researchers and practitioners in academia and industry

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Date de parution :

Ouvrage de 168 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

189,89 €

Ajouter au panier