| 书目名称 | Visual Inference for IoT Systems: A Practical Approach |
| 编辑 | Delia Velasco-Montero,Jorge Fernández-Berni,Angel |
| 视频video | http://file.papertrans.cn/984/983735/983735.mp4 |
| 概述 | Surveys the state-of-the-art of embedded vision based on deep learning.Describes strategies to leverage the limited resources of IoT devices.Offers detailed examples of deep-learning-based realization |
| 图书封面 |  |
| 描述 | .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... |
| 出版日期 | Book 2022 |
| 关键词 | Computer Vision; Embedded Vision; Smart Vision Sensors for IoT; Cyber-Physical Systems; Edge Vision; Inte |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-90903-1 |
| isbn_softcover | 978-3-030-90905-5 |
| isbn_ebook | 978-3-030-90903-1 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |