A New Method of Object Recognition Based on Deep Synergetic Neural Network

Zong-hui SHEN, Ji-cheng MENG, Yuan-zhang WEI

Abstract


We propose a new deep learning network, i.e. deep synergetic neural network (DSNN), for object recognition. DSNN is constructed by a top-down manner, and it can overcome the problem of pseudo-state with the traditional neural network. To verify the performance of DSNN in object recognition, experiments are performed on two famous databases, i.e. ORL face library and MNIST handwritten library. The experimental results show that the proposed DSNN outperforms the same class of algorithm DBN.

Keywords


Object recognition, Deep learning, Synergetic neural network.


DOI
10.12783/dtmse/ammme2016/6900

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