Visual Inference for IoT Systems: A Practical Approach (Hardcover, 1st ed. 2022)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	2022
First published:	2022
Authors:	Delia Velasco-Montero • Jorge Fernandez-Berni • Angel Rodriguez-Vazquez
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	159
Edition:	1st ed. 2022
ISBN-13:	978-3-03-090902-4
Categories:	Books > Computing & IT > Computer hardware & operating systems > General Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Computing & IT > Applications of computing > Image processing > General Promotions
LSN:	3-03-090902-6
Barcode:	9783030909024

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