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Algorithm Research & Explore
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354-358

Multi-view momentum contrast learning algorithm

Li Yongcai
Liu Xiangyang
School of Science, Hohai University, Nanjing 211100, China

Abstract

Comparing the similarity of different enhancements of the same image is the key to achieving remarkable results in contrastive learning. The traditional contrastive learning method uses two different views of the image. In order to learn more information of the image to improve the classification accuracy, based on MoCo, this paper presented multi-view momentum contrast learning algorithms. In each iteration, this paper used a query encoder and multiple momentum encoders to extract feature for multiple data enhancements of the image, so that it could use more data enhancements and negative samples in this iteration. And it used the optimized noise contrast estimation(InfoNCE) to calculate the loss, so that the query encoder could obtain feature representations which was more beneficial to downstream tasks. The query encoder network updated with gradient backhaul, and each momentum encoder updated with an improved momentum update formula to improve the generalization ability of the model. Experimental results show that using multi-view momentum contrastive learning can effectively improve the classification accuracy of the model.

Foundation Support

云南省重大科技专项(202002AE090010)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.07.0344
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 2
Section: Algorithm Research & Explore
Pages: 354-358
Serial Number: 1001-3695(2023)02-006-0354-05

Publish History

[2022-09-23] Accepted Paper
[2023-02-05] Printed Article

Cite This Article

李永财, 刘向阳. 多视图动量对比学习算法 [J]. 计算机应用研究, 2023, 40 (2): 354-358. (Li Yongcai, Liu Xiangyang. Multi-view momentum contrast learning algorithm [J]. Application Research of Computers, 2023, 40 (2): 354-358. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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