报告题目：Cognitive Foundations and Formal Theories of Human and Robot Visions
报告摘要：The neurological and cognitive mechanisms of visual information representation and manipulations in the visual cortex are fundamentally different from those of knowledge in the long-term memory. It is recognized that visual information is elicited and retained as feature frames rather than individual bitmap images. This talk presents the latest development of the Cognitive Vision Theory (CVT) that extends and synergizes the classical vision principles based on Dennis Gabor’s wavelength and orientation filters(1971, Nobel Prize Laureate in Physics) and David H. Hubel’s hypercolumn theory (1981, Nobel Prize Laureate in Physiology or Medicine).
This talk formally explains the visual information processing mechanisms in the brain. A Spike Frequency Modulation (SFM) theory is introduced to coherently link the pixel-based CCD mechanism of the retina to the Hubel feature representation in visual cortex throughout the entire neural pathways of human vision. Experiments on the CVT and SFM theories in both human and robotic visual information processing are rigorously elaborated. The basic studies on the CVT and SFM theories provide a new perspective for human and robot vision, which pave a way to novel image processing applications in AI, neural networks, image recognitions, sequence learning, computational intelligence, unmanned systems and robot vision.
报告题目：Cognitive Machine Learning and Reasoning by Cognitive Robots
报告摘要：It is recognized that the next generation of AI technologies and robotics will be driven by deep basic studies and novel mathematical means, because neither natural nor artificial intelligence can be adequately denoted and manipulated by pure numbers in R as in traditional approaches. This fundamental constraint for AI has led to systematic studies on the hierarchical framework of contemporary sciences of intelligence, knowledge, information, and data as well as underpinning denotational mathematics. It is discovered that AI may only mimic imperative and iterative intelligence. However, more sophisticated human intelligence according to the abstract intelligence (AI) theory [Wang. 2009], such as those of cognitive, causal, recursive, and inductive intelligence, had hardly been implemented by traditional computational intelligence. This talk presents a number of novel cognitive systems, which address the hard AI problems, encompassing cognitive robots (CR), cognitive machine learning engines (CMLE), cognitive neural networks (CNN),and applied cognitive systems.
王迎旭教授， ICIC（国际认知信息学与认知计算研究所）创始人兼总裁，加拿大卡尔加里大学全职教授，博士毕业于英国诺丁汉特伦特大学计算机科学专业。主要研究领域为认知信息学；大脑科学；软件科学等。发表500余篇相关领域的学术文章和36本著作，曾担任30余个国际会议的名誉主席，项目主席。通过与知名同行和领先的工业合作伙伴的深入合作，他领导了10多个国际、欧洲和加拿大研究项目。根据Research Gate的国际大数据，王迎旭教授是全球排名前2.5%的学者之一。