Visual Inference for IoT Systems: A Practical Approach - Delia Velasco-Montero,Jorge Fernández-Berni,Angel Rodríguez-Vázquez
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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 experim ... Full description
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Description
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.
More Information
| Author | Delia Velasco-Montero, Jorge Fernández-Berni, Angel Rodríguez-Vázquez |
|---|---|
| Publisher | Springer Nature Switzerland |
| Release year | 2022 |
| Cover type | Hardcover |
| EAN | 9783030909024 |