Visual Inference for IoT Systems: A Practical Approach
Springer International Publishing (Verlag)
978-3-030-90902-4 (ISBN)
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.
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.
| Erscheinungsdatum | 30.01.2022 |
|---|---|
| Zusatzinfo | XIII, 159 p. 59 illus., 57 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 421 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Netzwerke |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Technik ► Elektrotechnik / Energietechnik | |
| Schlagworte | computer vision • convolutional neural networks • Cyber-Physical Systems • Deep learning • deep neural networks • Edge Vision • Embedded Vision • Inference Performance • internet of things • Remote Animal Recognition • Smart Vision Sensors for IoT |
| ISBN-10 | 3-030-90902-6 / 3030909026 |
| ISBN-13 | 978-3-030-90902-4 / 9783030909024 |
| Zustand | Neuware |
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