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Research on glaucoma classification of college students based on deep convolutional neural network

Published: 13 April 2022 Publication History

Abstract

With the advancement of deep learning technology, using deep convolutional neural network to figure out image classification has always been a research hotspot. At present, the incidence rate of high myopia is increasing. High myopia can cause pathological changes of the eyeground, which can cause various eye diseases. Glaucoma is one of the diseases that seriously threaten the vision of college students. Glaucoma caused by myopia seriously threatens the vision of patients. However, because the process of diagnosing glaucoma needs to be manually realized by doctors and is very time-consuming, it is great necessity for us to realize fast diagnosis of glaucoma. Convolutional neural network has self-learning ability and can improve the diagnosis speed of glaucoma. In order to figure out this issue, this paper proposes a classification network based on deep convolutional neural network to promote the feature extraction ability of network, and realize the accurate diagnosis of glaucoma. Experiments show that our method has achieved good accuracy in the classification of glaucoma.

References

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cover image ACM Other conferences
CCEAI '22: Proceedings of the 6th International Conference on Control Engineering and Artificial Intelligence
March 2022
130 pages
ISBN:9781450385916
DOI:10.1145/3522749
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 13 April 2022

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Author Tags

  1. Convolutional neural network
  2. Deep learning
  3. Disease diagnosis
  4. Glaucoma
  5. Image classification

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