Multispectral Image Recognition Research Based on Biomimetic Pattern Recognition
Studies on learning problems from geometry perspective have attracted an ever increasing attention in machine learning, leaded by Biomimetic Pattern Recognition on information geometry. Biomimetic Pattern Recognition is a new model of Pattern Recognition based on matter cognition instead of matter classification. This new model is much closer to the function of human being, than traditional statistical Pattern Recognition using optimal separating as its main principlcThis paper proposes a high-dimensional descriptive way about multispectral image. Geometrical properties of high-dimensional structures underlying a set of samples are learned via successive projections from the higher dimension to the lower dimension until Clifford space, under guidance of the established properties and theorems in high-dimensional descriptive way. Specifically, we introduce a principle of homology continuity based on Clifford Algebra and provides a geometrical learning algorithm for specifying Clifford Algebra shapes, which is then applied to biomimetic pattern recognition. Experimental results are presented to show the efficiency of our theory.
Biomimetic Pattern Recognition multispectral image high-dimensional descriptive Clifford space hypercomplez
Wenming Cao Hao Feng
Jiaxing University.Jiaxing, Zhejiang, 100083, China Institute of Intelligent Information System, She Jiaxing University.Jiaxing, Zhejiang, 100083, China
国际会议
Second International Symposium on Electronic Commerce and Security(第二届电子商务与安全国际研究大会)(ISECS 2009)
南昌
英文
789-792
2009-05-22（万方平台首次上网日期，不代表论文的发表时间）