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Visual inference for IoT systems = a...

Velasco-Montero, Delia.

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Visual inference for IoT systems = a practical approach /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Visual inference for IoT systems/ by Delia Velasco-Montero, Jorge Fernandez-Berni, Angel Rodriguez-Vazquez.
Reminder of title:	a practical approach /
Author:	Velasco-Montero, Delia.
other author:	Fernandez-Berni, Jorge.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	xiii, 159 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Embedded Vision for the Internet of the Things: State-of-the-Art -- Hardware, Software, and Network Models for Deep-Learning Vision: A Survey -- Optimal Selection of Software and Models for Visual Interference -- Relevant Hardware Metrics for Performance Evaluation -- Prediction of Visual Interference Performance -- A Case Study: Remote Animal Recognition.
Contained By:	Springer Nature eBook
Subject:	Computer vision. -
Online resource:	https://doi.org/10.1007/978-3-030-90903-1
ISBN:	9783030909031

Visual inference for IoT systems = a practical approach /
Velasco-Montero, Delia.

Visual inference for IoT systemsa practical approach /[electronic resource] :by Delia Velasco-Montero, Jorge Fernandez-Berni, Angel Rodriguez-Vazquez. - Cham :Springer International Publishing :2022. - xiii, 159 p. :ill., digital ;24 cm.

Introduction -- Embedded Vision for the Internet of the Things: State-of-the-Art -- Hardware, Software, and Network Models for Deep-Learning Vision: A Survey -- Optimal Selection of Software and Models for Visual Interference -- Relevant Hardware Metrics for Performance Evaluation -- Prediction of Visual Interference Performance -- A Case Study: Remote Animal Recognition.

This book presents a systematic approach to the implementation of Internet of Things (IoT) devices achieving visual inference through deep neural networks. Practical aspects are covered, with a focus on providing guidelines to optimally select hardware and software components as well as network architectures according to prescribed application requirements. The monograph includes a remarkable set of experimental results and functional procedures supporting the theoretical concepts and methodologies introduced. A case study on animal recognition based on smart camera traps is also presented and thoroughly analyzed. In this case study, different system alternatives are explored and a particular realization is completely developed. Illustrations, numerous plots from simulations and experiments, and supporting information in the form of charts and tables make Visual Inference and IoT Systems: A Practical Approach a clear and detailed guide to the topic. It will be of interest to researchers, industrial practitioners, and graduate students in the fields of computer vision and IoT.

ISBN: 9783030909031

Standard No.: 10.1007/978-3-030-90903-1doiSubjects--Topical Terms:

540671
Computer vision.

LC Class. No.: TA1634 / .V45 2022

Dewey Class. No.: 006.37

Visual inference for IoT systems = a practical approach /
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100 1 $a Velasco-Montero, Delia. $3 3592813
245 1 0 $a Visual inference for IoT systems $h [electronic resource] : $b a practical approach / $c by Delia Velasco-Montero, Jorge Fernandez-Berni, Angel Rodriguez-Vazquez.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xiii, 159 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- Embedded Vision for the Internet of the Things: State-of-the-Art -- Hardware, Software, and Network Models for Deep-Learning Vision: A Survey -- Optimal Selection of Software and Models for Visual Interference -- Relevant Hardware Metrics for Performance Evaluation -- Prediction of Visual Interference Performance -- A Case Study: Remote Animal Recognition.
520 $a This book presents a systematic approach to the implementation of Internet of Things (IoT) devices achieving visual inference through deep neural networks. Practical aspects are covered, with a focus on providing guidelines to optimally select hardware and software components as well as network architectures according to prescribed application requirements. The monograph includes a remarkable set of experimental results and functional procedures supporting the theoretical concepts and methodologies introduced. A case study on animal recognition based on smart camera traps is also presented and thoroughly analyzed. In this case study, different system alternatives are explored and a particular realization is completely developed. Illustrations, numerous plots from simulations and experiments, and supporting information in the form of charts and tables make Visual Inference and IoT Systems: A Practical Approach a clear and detailed guide to the topic. It will be of interest to researchers, industrial practitioners, and graduate students in the fields of computer vision and IoT.
650 0 $a Computer vision. $3 540671
650 0 $a Internet of things. $3 2057703
650 1 4 $a Internet of Things. $3 3538511
650 2 4 $a Computer Vision. $3 3538524
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Fernandez-Berni, Jorge. $3 3592814
700 1 $a Rodriguez-Vazquez, Angel. $3 1569791
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-030-90903-1
950 $a Engineering (SpringerNature-11647)