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Automatic detection of exudates and hemorrhages in low‐contrast color fundus images using multi semantic convolutional neural network

  • Published:2022-01-10 Issue:6 Volume:34 Page:
  • ISSN:1532-0626
  • Container-title:Concurrency and Computation: Practice and Experience
  • language:en
  • Short-container-title:Concurrency and Computation

Author:

Selçuk Turab1ORCID,Beyoğlu Abdullah2,Alkan Ahmet1

Affiliation:

1. Department of Electrical‐Electronics Engineering Kahramanmaraş Sütçü İmam University Onikişubat Turkey

2. Department of Ophthalmology Kahramanmaraş Sütçü İmam University Onikişubat Turkey

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automatic Detection And Segmentation Of Retinal Manifestations Due To Diabetic Retinopathy;2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT);2023-05-25

2. A Survey on Diabetic Retinopathy Lesion Detection and Segmentation;Applied Sciences;2023-04-19

3. Deep learning for diabetic retinopathy assessments: a literature review;Multimedia Tools and Applications;2023-04-11

4. FunSwin: A deep learning method to analysis diabetic retinopathy grade and macular edema risk based on fundus images;Frontiers in Physiology;2022-07-25
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