TY  - BOOK
AU  - Velasco-Montero, Delia; 
AU  - Fernández-Berni, Jorge; 
AU  - Rodríguez-Vázquez, Angel
TI  - Visual inference for IOT systems : : a practical approach
SN  - 9783030909024
U1  - 006.37 
PY  - 2022///
CY  - Cham, Switzerland : 
PB  - Springer, 
KW  - Artificial intelligence
KW  - Computer vision
KW  - Internet of things
N1  - 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
N2  - 	
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.
ER  -