TY  - BOOK
AU  - Velasco-Montero,Delia
AU  - Fernández-Berni,Jorge
AU  - Rodríguez-Vázquez,Angel
ED  - SpringerLink (Online service)
TI  - Visual Inference for IoT Systems: A Practical Approach
SN  - 9783030909031
AV  - TA1634 
PY  - 2022///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Internet of things
KW  - Computer vision
KW  - Artificial intelligence
KW  - Internet of Things
KW  - Computer Vision
KW  - Artificial Intelligence
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
UR  - https://doi.org/10.1007/978-3-030-90903-1
ER  -