Published November 30, 2023 | Version CC-BY-NC-ND 4.0
Journal Open

Comparison of Various Deep Learning Models Used to Detect and Classify Keratoconus Disease

Creators

  • 1. Department of Information Science and Engineering, Engineering R. V. College of Engineering Bengaluru (Karnataka), India.

Contributors

Contact person:

Researcher:

  • 1. Department of Information Science and Engineering, Engineering R. V. College of Engineering Bengaluru (Karnataka), India.
  • 2. Department of Information Science and Engineering, Engineering R. V. College of Engineering Bengaluru (Karnataka), India

Description

Abstract: The corneal condition keratoconus results in both corneal thinning and bulging, along with symptoms like astigmatism, light sensitivity, blurred vision, etc. Your eyes can be impacted by genetic, environmental, and ageing-related problems because they are one of the most complicated organs in the human body. From little discomfort to more serious vision problems that could harm your eyesight, this can happen. The screening for keratoconus necessitates a thorough examination of the cornea using a variety of methods, including slip lamp analysis and corneal tomography. The goal of the study is to identify and categorize keratoconus using a variety of machine-learning methods.

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Additional details

Identifiers

DOI
10.35940/ijitee.L9745.11121223
ISSN
2278-3075

Dates

Accepted
2023-11-15
Manuscript received on 10 October 2023 | Revised Manuscript received on 18 October 2023 | Manuscript Accepted on 15 November 2023 | Manuscript published on 30 November 2023

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