This book presents the latest findings in the field of brain-inspired intelligence and visual perception (BIVP), and discusses novel research assumptions, including an introduction to brain science and the brain vision hypotheses. Moreover, it introduces readers to the theory and algorithms of BIVP – such as pheromone accumulation and iteration, neural cognitive computing mechanisms, the integration and scheduling of core modules, and brain-inspired perception, motion and control – in a step-by-step manner. Accordingly, it will appeal to university researchers, R&D engineers, undergraduate and graduate students; to anyone interested in robots, brain cognition or computer vision; and to all those wishing to learn about the core theory, principles, methods, algorithms, and applications of BIVP. 

Presents and applies the hypothesis of machine brain vision Integrates machine brain cognition with its visual perception Establishes a systematic framework of brain-inspired intelligence Links robots’ visual cognition with other core modules of machine brain vision Interprets and achieves brain-inspired intelligence as 3-Layer Intelligence

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