01913nas a2200229   4500000000100000000000100001008004100002260001200043653002700055653002400082653002100106653001800127653001500145100001300160700001600173245005300189856007900242300001000321490000600331520133200337022001401669       2023                            d  c12/202310aBio-Inspired Computing10aCognitive Computing10aNeural Computing10aDeep Learning10aMultimedia1 aYang Liu1 aJianshe Wei00aResearch on Brain and Mind Inspired Intelligence  uhttps://www.ijimai.org/journal/sites/default/files/2023-11/ijimai8_4_2.pdf  a17-320 v83 aTo address the problems of scientific theory, common technology and engineering application of multimedia and multimodal information computing, this paper is focused on the theoretical model, algorithm framework, and system architecture of brain and mind inspired intelligence (BMI) based on the structure mechanism simulation of the nervous system, the function architecture emulation of the cognitive system and the complex behavior imitation of the natural system. Based on information theory, system theory, cybernetics and bionics, we define related concept and hypothesis of brain and mind inspired computing (BMC) and design a model and framework for frontier BMI theory. Research shows that BMC can effectively improve the performance of semantic processing of multimedia and cross-modal information, such as target detection, classification and recognition. Based on the brain mechanism and mind architecture, a semantic-oriented multimedia neural, cognitive computing model is designed for multimedia semantic computing. Then a hierarchical cross-modal cognitive neural computing framework is proposed for cross-modal information processing. Furthermore, a cross-modal neural, cognitive computing architecture is presented for remote sensing intelligent information extraction platform and unmanned autonomous system.  a1989-1660