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Adaptive parameter computation for the automatic measure of the Tear Break-Up Time.

, , , , , , and . KES, volume 243 of Frontiers in Artificial Intelligence and Applications, page 1370-1379. IOS Press, (2012)

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On the Automation of the Tear Film Non-invasive Break-up Test., , , , , and . CBMS, page 185-188. IEEE Computer Society, (2014)Color Video Segmentation by Dissimilarity Based on Edges., , , , and . HAIS (2), volume 6077 of Lecture Notes in Computer Science, page 264-271. Springer, (2010)Multi-Modal Self-Supervised Pre-Training for Joint Optic Disc and Cup Segmentation in Eye Fundus Images., , , , and . ICASSP, page 961-965. IEEE, (2020)Deep Learning Models for Justified Referral in AI Glaucoma Screening., , , and . ISBI, page 1-3. IEEE, (2024)Adaptive parameter computation for the automatic measure of the Tear Break-Up Time., , , , , , and . KES, volume 243 of Frontiers in Artificial Intelligence and Applications, page 1370-1379. IOS Press, (2012)Region of interest-bounded COVID-19 lung screening using images from portable X-ray devices., , , , and . XoveTIC, volume 14 of Kalpa Publications in Computing, page 111-114. EasyChair, (2022)Break-Up Analysis of the Tear Film Based on Time, Location, Size and Shape of the Rupture Area., , , , and . ICIAR, volume 7950 of Lecture Notes in Computer Science, page 695-702. Springer, (2013)Automation of the tear film break-up time test., , , , and . ISABEL, page 123:1-123:5. ACM, (2011)Machine learning-based WENO5 scheme., , , , and . Comput. Math. Appl., (2024)Texture and Color Analysis for the Automatic Classification of the Eye Lipid Layer., , , , , and . IWANN (2), volume 6692 of Lecture Notes in Computer Science, page 66-73. Springer, (2011)