Review on Diabetic Retinopathy Detection through Deep Learning Techniques |
Author(s): |
| Vishal Barot , LDRP Institute of Technology and Research, Kadi Sarva Vishwavidyalaya; Pratik Modi, LDRP Institute of Technology and Research, Kadi Sarva Vishwavidyalaya; Hitesh Barot, LDRP Institute of Technology and Research, Kadi Sarva Vishwavidyalaya; Piyush Kapadiya, LDRP Institute of Technology and Research, Kadi Sarva Vishwavidyalaya; Mehul P. Barot, LDRP Institute of Technology and Research, Kadi Sarva Vishwavidyalaya |
Keywords: |
| Diabetic Retinopathy (DR), Deep Learning Techniques |
Abstract |
|
Diabetic retinopathy (DR) is a common complication of diabetes that can lead to vision loss if not detected and treated early. Deep learning techniques have shown great promise in the automated detection of DR from retinal images, offering a potential solution to the growing healthcare challenge. This survey paper provides an in-depth analysis of various deep learning methods and approaches used for diabetic retinopathy detection. We categorize the techniques into two main columns: Image-based and Non-image-based approaches, to offer a comprehensive understanding of the field. |
Other Details |
|
Paper ID: LDRPTCP047 Published in: Conference 12 : LDRP TECON23 Publication Date: 23/12/2023 Page(s): 240-244 |
Article Preview |
|
Download Article |
|
|
