International Journal of Electrical, Electronics and Data Communication (IJEEDC)
eISSN:2320-2084 , pISSN:2321-2950
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Statistics report
Jan. 2021
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 93
Paper Published : 1465
No. of Authors : 3971
  Journal Paper

Paper Title
Detection of Diabetic Retinopathy in Fundus Images using Extreme Learning Machines

Diabetic Retinopathy (DR) is the term used to describe the retinal damage due to diabetes. Initially, diabetic retinopathy may cause none to mild symptoms but sight loss at an advanced stage. Hence detecting lesions automatically in retinal images can assist in diagnosis and screening of DR at an early stage. The detection of the different lesions in fundus images is therefore of interest. This project proposes the pre-processing of the image using a Median Filter and Contrast Limited Adaptive Histogram Equalization(CLAHE), optic disc detection using Hough Transform, feature extraction using Gray-Level Co-Occurrence Matrix (GLCM) and Extreme Learning Machines (ELM) for classification. Keywords - Contrast Limited Adaptive Histogram Equalization (CLAHE), Diabetic Retinopathy, Gray Level Co-Occurrence Matrix (GLCM), Extreme Learning Machines (ELM), Median Filter.

Author - Lisa Maria Macedo, Amita Dessai

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| Published on 2019-09-24
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