This book seeks to interpret connections between the machine brain, mind
and vision in an alternative way and promote future research into the
Interdisciplinary Evolution of Machine Brain (IEMB). It gathers novel
research on IEMB, and offers readers a step-by-step introduction to the
theory and algorithms involved, including data-driven approaches in
machine learning, monitoring and understanding visual environments,
using process-based perception to expand insights, mechanical
manufacturing for remote sensing, reconciled connections between the
machine brain, mind and vision, and the interdisciplinary evolution of
machine intelligence.
This book is intended for researchers, graduate students and engineers
in the fields of robotics, Artificial Intelligence and brain science, as
well as anyone who wishes to learn the core theory, principles, methods,
algorithms, and applications of IEMB.