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  Published Paper Details:

  Paper Title

DIABETIC RETINOPATHY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH RECTIFIED LINEAR UNIT AND SOFTMAX AS AN ACTIVATION FUNCTION

  Authors

  Tejas Phirke,  Omkar Parte,  Aniket Garje,  Sanjay .S. Kadam

  Keywords

Diabetic Retinopathy, Convolutional Neural Network, Rectified Linear Unit

  Abstract


Diabetic retinopathy (DR) is a type of disease which is spreading in significant numbers, it not only spreads in India but also in all over the world. The increase in the spread of disease can lead to many deaths since there is no proper medication that can heal the patient. Diabetic Retinopathy is a disease that occurs due to irregular blood flow in retina vessels and weakens the retina. Due to the irregularities in the blood vessels patients face difficulty in the vision loss and can also make the patient blind. In this paper, we used deep learning which includes Convolutional Neural Network (CNN) provides better accuracy by using Rectified Linear Unit (ReLU). As there are various image classification techniques but CNN provides much better accuracy from other techniques. For detecting a particular part of the eye, it needs advanced mechanisms and tools. The main objective is to provide lucid image classification among other images with better accuracy.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2105209

  Paper ID - 206519

  Page Number(s) - c66-c70

  Pubished in - Volume 9 | Issue 5 | May 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Tejas Phirke,  Omkar Parte,  Aniket Garje,  Sanjay .S. Kadam,   "DIABETIC RETINOPATHY DETECTION USING CONVOLUTIONAL NEURAL NETWORK WITH RECTIFIED LINEAR UNIT AND SOFTMAX AS AN ACTIVATION FUNCTION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 5, pp.c66-c70, May 2021, Available at :http://www.ijcrt.org/papers/IJCRT2105209.pdf

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ISSN: 2320-2882
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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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