Computer Science ›› 2016, Vol. 43 ›› Issue (Z6): 46-50.doi: 10.11896/j.issn.1002-137X.2016.6A.010

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Research on Image Classification Algorithm Based on Semi-supervised Deep Belief Network

ZHU Chang-bao, CHENG Yong and GAO Qiang   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In recent years,the deep learning to get a successful application in image,voice,video and other unstructured data,has become a hot topic of machine learning and data mining.As a supervised learning model,the successful deep learning applications often require a larger set of high-quality training.Based on this situation,we studied deep belief network composed of more restricted Boltzmann machines,and combined with the thought of semi-supervised learning,we used smaller training set to improve the classification accuracy of depth network model.We used Knn,SVM and pHash three methods to study the non-labeled data set.And the result shows that the semi-supervised deep belief networks increases image classification accuracy by about 3% compared with the traditional network with more restricted Boltzmann machine.

Key words: Semi-supervised,Deep belief networks,Restricted boltzmann machine

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