東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Robot vision." ]

切換: 標籤 | MARC模式 | ISBD

Multimodal computational attention f...

Schauerte, Boris.

FindBook

Google Book

Amazon

博客來

Multimodal computational attention for scene understanding and robotics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multimodal computational attention for scene understanding and robotics/ by Boris Schauerte.
作者:	Schauerte, Boris.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	xxiv, 203 p. :ill. (some col.), digital ;24 cm.
內容註:	Introduction -- Background -- Bottom-up Audio-Visual Attention for Scene Exploration -- Multimodal Attention with Top-Down Guidance -- Conclusion -- Applications -- Dataset Overview.
Contained By:	Springer eBooks
標題:	Robot vision. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-33796-8
ISBN:	9783319337968

Multimodal computational attention for scene understanding and robotics
Schauerte, Boris.

Multimodal computational attention for scene understanding and robotics[electronic resource] /by Boris Schauerte. - Cham :Springer International Publishing :2016. - xxiv, 203 p. :ill. (some col.), digital ;24 cm. - Cognitive systems monographs,v.301867-4925 ;. - Cognitive systems monographs ;v.16..

Introduction -- Background -- Bottom-up Audio-Visual Attention for Scene Exploration -- Multimodal Attention with Top-Down Guidance -- Conclusion -- Applications -- Dataset Overview.

This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.

ISBN: 9783319337968

Standard No.: 10.1007/978-3-319-33796-8doiSubjects--Topical Terms:

674122
Robot vision.

LC Class. No.: TJ211.3

Dewey Class. No.: 629.892637

Multimodal computational attention for scene understanding and robotics
LDR:01994nmm a2200325 a 4500 001 2038163
003 DE-He213
005 20161020140314.0
006 m d
007 cr nn 008maaau
008 161209s2016 gw s 0 eng d
020 $a 9783319337968 $q (electronic bk.)
020 $a 9783319337944 $q (paper)
024 7 $a 10.1007/978-3-319-33796-8 $2 doi
035 $a 978-3-319-33796-8
040 $a GP $c GP
041 0 $a eng
050 4 $a TJ211.3
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 629.892637 $2 23
090 $a TJ211.3 $b .S313 2016
100 1 $a Schauerte, Boris. $3 2195135
245 1 0 $a Multimodal computational attention for scene understanding and robotics $h [electronic resource] / $c by Boris Schauerte.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xxiv, 203 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Cognitive systems monographs, $x 1867-4925 ; $v v.30
505 0 $a Introduction -- Background -- Bottom-up Audio-Visual Attention for Scene Exploration -- Multimodal Attention with Top-Down Guidance -- Conclusion -- Applications -- Dataset Overview.
520 $a This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.
650 0 $a Robot vision. $3 674122
650 0 $a Human-robot interaction. $3 1612845
650 1 4 $a Engineering. $3 586835
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Robotics and Automation. $3 1066695
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Image Processing and Computer Vision. $3 891070
650 2 4 $a Pattern Recognition. $3 891045
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Cognitive systems monographs ; $v v.16. $3 1567806
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-33796-8
950 $a Engineering (Springer-11647)