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.
General
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