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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.
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.
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