Analysis and Detection of Glaucoma from Fundus Eye Image by Cup to Disc Ratio by Unsupervised Machine Learning-Reference-Cited by-同舟云学术

Analysis and Detection of Glaucoma from Fundus Eye Image by Cup to Disc Ratio by Unsupervised Machine Learning

Published:2022-07-29 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Data Science and Information System (ICDSIS)
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Author:

Surendiran J.¹,Meena M.²

Affiliation:

1. HKBK CE,Department of ECE,Bangalore,India

2. VISTAS,Department of ECE,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9915554/9915796/09915887.pdf?arnumber=9915887

Reference16 articles.

1. Fast segmentation of texture image regions based on hill-climbing

2. Hill-climbing algorithm for efficient color-based image segmentation;ohashi;International Conference on Signal Processing Pattern Recognition and Applications,0

3. Automatic detection of glaucoma using Fundus image;ganeshbabu;European Journal of Scientific Research,0

4. Automatic Exudate Detection from Non-dilated Diabetic Retinopathy Retinal Images Using Fuzzy C-means Clustering

5. Fuzzy c-means clustering with spatial information for image segmentation

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