Research on Brain and Mind Inspired Intelligence

被引：3
作者：
Liu, Yang [1 ]
Wei, Jianshe [2 ]
机构：
[1] Henan Univ, Coll Comp & Informat Engn, Henan Key Lab Big Data Anal & Proc, Kaifeng, Peoples R China
[2] Henan Univ, Sch Life Sci, Inst Brain Sci Res, Lab Brain Funct & Mol Neurodegenerat, Kaifeng, Peoples R China
来源：
INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE | 2023年 / 8卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Brain and Mind Inspired Intelligence; Brain and Mind Inspired Computing; Cognitive Computing; Cross-Modal Cognitive Neural Computing; Deep Learning; Multimedia Neural Cognitive Computing; TRIUNE BRAIN; NETWORKS; MODEL;
D O I：
10.9781/ijimai.2023.07.004
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
To 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.
引用
收藏
页码：17 / 32
页数：16
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