Visual Inference for IoT Systems: A Practical Approach
| Autor: | Delia Velasco-Montero, Jorge Fernández-Berni, Angel Rodríguez-Vázquez |
|---|---|
| EAN: | 9783030909031 |
| eBook Format: | |
| Sprache: | Englisch |
| Produktart: | eBook |
| Veröffentlichungsdatum: | 28.01.2022 |
| Kategorie: | |
| Schlagworte: | Computer Vision;Embedded Vision;Smart Vision Sensors for IoT;Cyber-Physical Systems;Edge Vision;Internet of Things;Deep Neural Networks;Deep Learning;Convolutional Neural Networks;Inference Performance;Remote Animal Recognition |
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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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