Artificial Vision and Language Processing for Robotics: Create end-to-end systems that can power robots with artificial vision and deep learning techniques

Álvaro Morena Alberola

ISBN 10: 183855226X / ISBN 13: 9781838552268

Verlag: Packt Publishing Limited, 2019

Beschreibung

2019. Paperback. . . . . . Books ship from the US and Ireland.

Bestandsnummer des Verkäufers V9781838552268

Bibliografische Details

• Titel: Artificial Vision and Language Processing for Robotics: Create end-to-end systems that can power robots with artificial vision and deep learning techniques
• Verlag: Packt Publishing Limited
• Erscheinungsjahr: 2019
• Sprache: Englisch
• ISBN-10: 183855226X
• ISBN-13: 9781838552268
• Einband: Softcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

Artificial Vision and Language Processing for Robotics will help you train and deploy models that are built with advanced deep learning techniques and integrate them in a unified end-to-end application. With this book, you will learn all about the three hottest topics of artificial intelligence: convolutional neural networks, recurrent neural ...

Über die Autorinnen und Autoren

Álvaro 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. Álvaro 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.

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.

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.