Visual Inference for IoT Systems: A Practical Approach
Produktnummer:
187c680dc5efaf41858b6503b9192d7945
Autor: | Fernández-Berni, Jorge Rodríguez-Vázquez, Angel Velasco-Montero, Delia |
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Themengebiete: | Computer Vision Convolutional Neural Networks Cyber-Physical Systems Deep Learning Deep Neural Networks Edge Vision Embedded Vision Inference Performance Internet of Things Smart Vision Sensors for IoT |
Veröffentlichungsdatum: | 29.01.2022 |
EAN: | 9783030909024 |
Sprache: | Englisch |
Seitenzahl: | 159 |
Produktart: | Gebunden |
Verlag: | Springer International Publishing |
Produktinformationen "Visual Inference for IoT Systems: A Practical Approach"
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.

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