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Visual Inference for IoT Systems: A Practical Approach
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Visual Inference for IoT Systems: A Practical Approach/ by Delia Velasco-Montero, Jorge Fernández-Berni, Angel Rodríguez-Vázquez.
作者:
Velasco-Montero, Delia.
其他作者:
Rodríguez-Vázquez, Angel.
面頁冊數:
XIII, 159 p. 59 illus., 57 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Artificial Intelligence. -
電子資源:
https://doi.org/10.1007/978-3-030-90903-1
ISBN:
9783030909031
Visual Inference for IoT Systems: A Practical Approach
Velasco-Montero, Delia.
Visual Inference for IoT Systems: A Practical Approach
[electronic resource] /by Delia Velasco-Montero, Jorge Fernández-Berni, Angel Rodríguez-Vázquez. - 1st ed. 2022. - XIII, 159 p. 59 illus., 57 illus. in color.online resource.
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.
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.
ISBN: 9783030909031
Standard No.: 10.1007/978-3-030-90903-1doiSubjects--Topical Terms:
646849
Artificial Intelligence.
LC Class. No.: TK5105.8857
Dewey Class. No.: 004.678
Visual Inference for IoT Systems: A Practical Approach
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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.
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