Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in an Unknown Environment - Rilegato

Wang, Xiaochun; Wang, Xiali; Wilkes, Don Mitchell

 
9789811392160: Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in an Unknown Environment
Rilegato
ISBN 10: 9811392161 ISBN 13: 9789811392160
Casa editrice: Springer Nature, 2019

Sinossi

This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene recognition. The respective chapters highlight the latest developments in vision-based machine perception and machine learning research for localization applications, and cover such topics as: image-segmentation-based visual perceptual grouping for the efficient identification of objects composing unknown environments; classification-based rapid object recognition for the semantic analysis of natural scenes in unknown environments; the present understanding of the Prefrontal Cortex working memory mechanism and its biological processes for human-like localization; and the application of this present understanding to improve mobile robot localization. The book also features a perspective on bridging the gap between feature representations and decision-making using reinforcement learning, laying the groundwork for future advances in mobile robot navigation research.

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Informazioni sull?autore

Xiaochun Wang received her BS degree from Beijing University and the PhD degree from the Department of Electrical Engineering and Computer Science, Vanderbilt University. She is currently an associate professor of School of Software Engineering at Xi’an Jiaotong University. Her research interests are in computer vision, signal processing, and pattern recognition.


Xia Li Wang received the PhD degree from the Department of Computer Science, Northwest University, China, in 2005. He is a faculty member in the Department of Computer Science, Changan University, China. His research interests are in computer vision, signal processing, intelligent traffic system, and pattern recognition.

D. Mitchell Wilkes received the BSEE degree from Florida Atlantic, and the MSEE and PhD degrees from Georgia Institute of Technology. His research interests include digital signal processing, image processing and computer vision, structurally adaptive systems, sonar, as well as signal modeling. He is a member of the IEEE and a faculty member at the Department of Electrical Engineering and Computer Science, Vanderbilt University. He is a member of the IEEE.

Dalla quarta di copertina

This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene recognition. The respective chapters highlight the latest developments in vision-based machine perception and machine learning research for localization applications, and cover such topics as: image-segmentation-based visual perceptual grouping for the efficient identification of objects composing unknown environments; classification-based rapid object recognition for the semantic analysis of natural scenes in unknown environments; the present understanding of the Prefrontal Cortex working memory mechanism and its biological processes for human-like localization; and the application of this present understanding to improve mobile robot localization. The book also features a perspective on bridging the gap between feature representations and decision-making using reinforcement learning, laying the groundwork for future advances in mobile robot navigation research.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer Nature
Data di pubblicazione
2019
Lingua
Inglese
ISBN 10 
9811392161
ISBN 13 
9789811392160
Rilegatura
Copertina rigida
Numero edizione
1
Numero di pagine
352
Contatto del produttore
non disponibile
Persona responsabile
ProductSafety@springernature.com
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Altre edizioni note dello stesso titolo

9789811392191: Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment

Edizione in evidenza

ISBN 10:  9811392196 ISBN 13:  9789811392191
Casa editrice: Springer, 2020
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