國立虎尾科技大學 |

Near-sensor and In-sensor Computing

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Near-sensor and In-sensor Computing/ edited by Yang Chai, Fuyou Liao.
其他作者:	Chai, Yang.
面頁冊數:	V, 240 p. 132 illus., 115 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Electronic circuits. -
電子資源:	https://doi.org/10.1007/978-3-031-11506-6
ISBN:	9783031115066

Near-sensor and In-sensor Computing
Near-sensor and In-sensor Computing[electronic resource] /edited by Yang Chai, Fuyou Liao. - 1st ed. 2022. - V, 240 p. 132 illus., 115 illus. in color.online resource.

Introduction (Fundamentals of near-/in-sensor computing) -- Neuromorphic vision sensors I -- Neuromorphic vision sensors Ⅱ -- Neuromorphic audio sensors -- Neuromorphic pressure sensors -- Neuromorphic chemical sensors -- Reconfigurable neural networks -- Convolutional neural networks -- Spike neural networks -- Integration technology of near-/in-sensor computing.

This book provides a detailed introduction to near-sensor and in-sensor computing paradigms, their working mechanisms, development trends and future directions. The authors also provide a comprehensive review of current progress in this area, analyze existing challenges in the field, and offer possible solutions. Readers will benefit from the discussion of computing approaches that intervene in the vicinity of or inside sensory networks to help process data more efficiently, decreasing power consumption and reducing the transfer of redundant data between sensing and processing units. Provides readers with a detailed introduction to the near-sensor and in-sensor computing paradigms; Includes in-depth and comprehensive summaries of the state-of-the-art development in this field; Discusses and compares various neuromorphic sensors and neural networks: Describes integration technology for near-/in-sensor computing; Reveals the relationship between near-/in-sensor computing and other computing paradigms, such as neuromorphic computing, edge computing, intuitive computing, and in-memory computing.

ISBN: 9783031115066

Standard No.: 10.1007/978-3-031-11506-6doiSubjects--Topical Terms:

563332
Electronic circuits.

LC Class. No.: TK7867-7867.5

Dewey Class. No.: 621.3815

Near-sensor and In-sensor Computing
LDR:02822nam a22003975i 4500 001 1084784
003 DE-He213
005 20221027130735.0
007 cr nn 008mamaa
008 221228s2022 sz | s |||| 0|eng d
020 $a 9783031115066 $9 978-3-031-11506-6
024 7 $a 10.1007/978-3-031-11506-6 $2 doi
035 $a 978-3-031-11506-6
050 4 $a TK7867-7867.5
072 7 $a TJFC $2 bicssc
072 7 $a TEC008010 $2 bisacsh
072 7 $a TJFC $2 thema
082 0 4 $a 621.3815 $2 23
245 1 0 $a Near-sensor and In-sensor Computing $h [electronic resource] / $c edited by Yang Chai, Fuyou Liao.
250 $a 1st ed. 2022.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a V, 240 p. 132 illus., 115 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Introduction (Fundamentals of near-/in-sensor computing) -- Neuromorphic vision sensors I -- Neuromorphic vision sensors Ⅱ -- Neuromorphic audio sensors -- Neuromorphic pressure sensors -- Neuromorphic chemical sensors -- Reconfigurable neural networks -- Convolutional neural networks -- Spike neural networks -- Integration technology of near-/in-sensor computing.
520 $a This book provides a detailed introduction to near-sensor and in-sensor computing paradigms, their working mechanisms, development trends and future directions. The authors also provide a comprehensive review of current progress in this area, analyze existing challenges in the field, and offer possible solutions. Readers will benefit from the discussion of computing approaches that intervene in the vicinity of or inside sensory networks to help process data more efficiently, decreasing power consumption and reducing the transfer of redundant data between sensing and processing units. Provides readers with a detailed introduction to the near-sensor and in-sensor computing paradigms; Includes in-depth and comprehensive summaries of the state-of-the-art development in this field; Discusses and compares various neuromorphic sensors and neural networks: Describes integration technology for near-/in-sensor computing; Reveals the relationship between near-/in-sensor computing and other computing paradigms, such as neuromorphic computing, edge computing, intuitive computing, and in-memory computing.
650 0 $a Electronic circuits. $3 563332
650 0 $a Cooperating objects (Computer systems). $3 1387590
650 0 $a Solid state physics. $3 641431
650 1 4 $a Electronic Circuits and Systems. $3 1366689
650 2 4 $a Cyber-Physical Systems. $3 1387591
650 2 4 $a Electronic Devices. $3 1366460
700 1 $a Chai, Yang. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1391165
700 1 $a Liao, Fuyou. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1391166
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783031115059
776 0 8 $i Printed edition: $z 9783031115073
776 0 8 $i Printed edition: $z 9783031115080
856 4 0 $u https://doi.org/10.1007/978-3-031-11506-6
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)