Morena Alberola / Alvaro Morena Alberola / Molina Gallego | Artificial Vision and Language Processing for Robotics | E-Book | sack.de
E-Book

E-Book, Englisch, 356 Seiten

Morena Alberola / Alvaro Morena Alberola / Molina Gallego Artificial Vision and Language Processing for Robotics

Create end-to-end systems that can power robots with artificial vision and deep learning techniques
1. Auflage 2019
ISBN: 978-1-83855-766-9
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

Create end-to-end systems that can power robots with artificial vision and deep learning techniques

E-Book, Englisch, 356 Seiten

ISBN: 978-1-83855-766-9
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)



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Weitere Infos & Material


Table of Contents - Fundamentals of Robotics
- Introduction to Computer Vision
- Fundamentals of Natural Language Processing
- Neural Networks with NLP
- Convolutional Neural Networks
- Robot Operating System
- Build a Conventional Agent to Manage the Robot
- Object Recognition to Guide a Robot Using CNNs
- Computer Vision for Robotics


Morena Alberola Álvaro:
lvaro Morena Alberola is a computer engineer and loves robotics and artificial intelligence. Currently, he is working as a software developer. He is extremely interested in the core part of AI, which is based on artificial vision. lvaro likes working with new technologies and learning how to use advanced tools. He perceives robotics as a way of easing human lives; a way of helping people perform tasks that they cannot do on their own.Molina Gallego Gonzalo:
Gonzalo Molina Gallego is a computer science graduate and specializes in artificial intelligence and natural language processing. He has experience of working on text-based dialog systems, creating conversational agents, and advising good methodologies. Currently, he is researching new techniques on hybrid-domain conversational systems. Gonzalo thinks that conversational user interfaces are the future.Garay Maestre Unai:
Unai Garay Maestre is a computer science graduate and specializes in the field of artificial intelligence and computer vision. He successfully contributed to the CIARP conference of 2018 with a paper that takes a new approach to data augmentation using variational autoencoders. He also works as a machine learning developer using deep neural networks applied to images.



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