Classification Method Based on Multilayer Tree-Structured Neural Network for Remote Sensing Images of Tianjin Development Area

Classification has been widely applied in images information mining. In this paper, the classification methods based on multilayer tree-structured neural network for remote sensing images of Tianjin development area is presented as an extended version of the classification algorithms in neural network, which has a dynamic tree-structure generated during the training process and its' growth speed can be controlled through the weight of network, and the user can get the hierarchical results through changing the weight of network in different steps.