To address modeling problems of brain-inspired intelligence, this thesis is focused on researching in the semantic-oriented framework design for multimedia and multimodal information. The Multimedia Neural Cognitive Computing (MNCC) model was designed based on the nervous mechanism and cognitive architecture. Furthermore, the semantic-oriented hierarchical Cross-modal Neural Cognitive Computing (CNCC) framework was proposed based on MNCC model, and formal description and analysis for CNCC framework was given. It would effectively improve the performance of semantic processing for multimedia and cross-modal information, and has far-reaching significance for exploration and realization brain-inspired computing.
翻译:为解决大脑启发型智力的建模问题,该论文的重点是研究多媒体和多式联运信息以语义为导向的框架设计,多媒体神经认知计算模型(MNCC)是根据神经机制和认知结构设计的,此外,基于MNCC模型提出了注重语义的跨模式等级跨模式神经认知计算(CNCC)框架,为CNCC框架提供了正式描述和分析,将有效改善多媒体和跨模式信息语义处理的性能,并对探索和实现脑动计算具有深远意义。