Sundar Singh Sheeba Jeya Sophia's scientific contributions
What is this page?
This page lists the scientific contributions of an author, who either does not have a ResearchGate profile, or has not yet added these contributions to their profile.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
Publications (2)
One of the most serious eye illnesses, glaucoma affects the astrocytes and optic nerve fibres, causing irreversible damage to the eyes. As a result, glaucoma early identification is crucial in the medical industry. Retinal image-based detection falls within the category of non-invasive ways of detection among the many techniques. Automatic periodic...
Glaucoma is an irreversible blindness that affects the people over the age of 40 years. Many approaches are proposed to detect glaucoma in image by dealing with its complex data. Redundancy is the major problem in medical image which could lead to increased false positive and false negative rates. This paper proposed a three-structure CNN optimized...
Citations
... Spectral indices were employed to detect the pattern and compare it with baseline versions. SIFT and RFSO classifiers [13] were introduced by the researchers to identify glaucoma at its early occurrence along with the layer thickness of the retina. The machine learning feature extraction models are used to extract 18 retinal features, including histograms and lesions, to perform a classification task. ...