國立高雄大學圖資館 |

Language: English

Back

Machine learning-based natural scene...

SpringerLink (Online service)

Machine learning-based natural scene recognition for mobile robot localization in an unknown environment

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning-based natural scene recognition for mobile robot localization in an unknown environmentby Xiaochun Wang, Xiali Wang, Don Mitchell Wilkes.
Author:	Wang, Xiaochun.
other author:	Wang, Xiali.
Published:	Singapore :Springer Singapore :2020.
Description:	xxii, 328 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Machine learning.
Online resource:	https://doi.org/10.1007/978-981-13-9217-7
ISBN:	9789811392177$q(electronic bk.)

Machine learning-based natural scene recognition for mobile robot localization in an unknown environment
Wang, Xiaochun.

Machine learning-based natural scene recognition for mobile robot localization in an unknown environment[electronic resource] /by Xiaochun Wang, Xiali Wang, Don Mitchell Wilkes. - Singapore :Springer Singapore :2020. - xxii, 328 p. :ill. (some col.), digital ;24 cm.

Part I Introduction -- Part II Unsupervised Learning -- Part III Supervised Learning and Semi-Supervised Learning -- Part IV Reinforcement Learning.

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.

ISBN: 9789811392177$q(electronic bk.)

Standard No.: 10.1007/978-981-13-9217-7doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 629.892

Machine learning-based natural scene recognition for mobile robot localization in an unknown environment
LDR:02230nmm a2200325 a 4500 001 577716
003 DE-He213
005 20200220161257.0
006 m d
007 cr nn 008maaau
008 201203s2020 si s 0 eng d
020 $a 9789811392177$q(electronic bk.)
020 $a 9789811392160$q(paper)
024 7 $a 10.1007/978-981-13-9217-7 $2 doi
035 $a 978-981-13-9217-7
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a TJFM1 $2 bicssc
072 7 $a TEC037000 $2 bisacsh
072 7 $a TJFM1 $2 thema
082 0 4 $a 629.892 $2 23
090 $a Q325.5 $b .W246 2020
100 1 $a Wang, Xiaochun. $3 866223
245 1 0 $a Machine learning-based natural scene recognition for mobile robot localization in an unknown environment $h [electronic resource] / $c by Xiaochun Wang, Xiali Wang, Don Mitchell Wilkes.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a xxii, 328 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Part I Introduction -- Part II Unsupervised Learning -- Part III Supervised Learning and Semi-Supervised Learning -- Part IV Reinforcement Learning.
520 $a 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.
650 0 $a Machine learning. $3 188639
650 0 $a Mobile robots. $3 199828
650 1 4 $a Robotics and Automation. $3 357111
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 274492
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Robotics. $3 181952
650 2 4 $a Machine Learning. $3 833608
700 1 $a Wang, Xiali. $3 866224
700 1 $a Wilkes, Don Mitchell. $3 866225
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-981-13-9217-7
950 $a Intelligent Technologies and Robotics (Springer-42732)