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논문검색

Image Retrieval Based on Deep Belief Networks

초록

영어

According to the local and global feature of image, matching the image from a lot image library, this is the image retrieval task; however, the image retrieval need to search the information in the database, we need to find a method for efficient information retrieval. Deep belief network according to the characteristic of the initiative, through the method of training a multilayer neural network to process large amounts of data, and it is very efficient, in this article, as to the characteristics of image local features and global features, it gives a deep belief network image retrieval algorithm, the experiment verify the effectiveness of the algorithm.

목차

Abstract
 1. Introduction
 2. Related Works
  2.1 The Research Status of Deep Neural Network
  2.2 The Research Status of Image Retrieval
 3. The Proposed Scheme
  3.1 The Input of Deep Belief Network
  3.2 The Determination of Learning Network Layer
  3.3 Setting Hidden Nodes
  3.4 Adaptive Learning Method
 4. Experiment Results and Analysis
 5. Conclusion
 References

저자정보

  • Sun Ting School of computer science and technology, Zhoukou Normal University, Zhoukou, Henan,466001, China
  • Qi Yingchun School of computer science and technology, Zhoukou Normal University, Zhoukou, Henan,466001, China

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