A structurally adaptive neural tree for the recognition of large character set

This paper presents an adaptive self-organizing neural tree and its application to character recognition. The neural tree is suitable for hierarchical classification and it can grow and shrink to adapt to the changing environment. It also performs parametric adaptation to cope with small changes in the environment. When applied to character pattern recognition, it shows promising performance. >