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

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Puja G. Ambalgekar
Ashwini K B

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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[1]
Puja G. Ambalgekar and Ashwini K B , Trans., “Comparison of Various Deep Learning Models Used to Detect and Classify Keratoconus Disease”, IJITEE, vol. 12, no. 12, pp. 1–5, Dec. 2023, doi: 10.35940/.
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How to Cite

[1]
Puja G. Ambalgekar and Ashwini K B , Trans., “Comparison of Various Deep Learning Models Used to Detect and Classify Keratoconus Disease”, IJITEE, vol. 12, no. 12, pp. 1–5, Dec. 2023, doi: 10.35940/.
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References

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