A Novel Approach for Early Recognition of Cataract using VGG-16 and Custom User-based Region of Interest

Author:

Paul Jacob Aaron1,Bansal Aryan1,Malhotra Ruchika1

Affiliation:

1. Department of Software Engineering, Delhi Technological University, India

Publisher

ACM

Reference19 articles.

1. Edupuganti, V.G. , Chawla , A., Kale, A. , 2018 . Automatic optic disk and cup segmentation of fundus images using deep learning , in: 2018 IEEE International Conference on Image Processing, ICIP 2018 , Athens, Greece , October 7-10, 2018, IEEE. pp. 2227– 2231 .URL: https://doi.org/10.1109/ICIP.2018.8451753, doi: 10.1109/ICIP.2018.8451753. Edupuganti, V.G., Chawla, A., Kale, A., 2018. Automatic optic disk and cup segmentation of fundus images using deep learning, in: 2018 IEEE International Conference on Image Processing, ICIP 2018, Athens, Greece, October 7-10, 2018, IEEE. pp. 2227–2231.URL: https://doi.org/10.1109/ICIP.2018.8451753, doi: 10.1109/ICIP.2018.8451753.

2. Linglin Zhang , "Automatic cataract detection and grading using Deep Convolutional Neural Network," 2017 IEEE 14th International Conference on Networking , Sensing and Control (ICNSC) , 2017 , pp. 60 - 65 , doi: 10.1109/ICNSC.2017.8000068. Linglin Zhang , "Automatic cataract detection and grading using Deep Convolutional Neural Network," 2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC), 2017, pp. 60-65, doi: 10.1109/ICNSC.2017.8000068.

3. Multi-label ocular disease classification with a dense correlation deep neural network

4. Chorage, S., Khot, S. S. : Detection of diabetic retinopathy and cataract by vessel extraction from fundus images . In: 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA) , vol. 1 , IEEE, pp. 638– 641 ( 2017 ) Chorage, S., Khot, S.S.: Detection of diabetic retinopathy and cataract by vessel extraction from fundus images. In: 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA), vol. 1, IEEE, pp. 638–641 (2017)

5. ImageNet Large Scale Visual Recognition Challenge

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