Anomaly Detection in Red Reflex Images Using Deep Learning Approaches

Kriangsakdachai, S.; Ayudhya, S. P. N.; Kusakunniran, W.; Ayudhya, W. D. N.; Chantrasagul, C.; Manasboonpermpool, R.; Sathianvichitr, K.; Sangsre, P.; Surachatkumtonekul, T.

Kriangsakdachai, S.; Ayudhya, S. P. N.; Kusakunniran, W.; Ayudhya, W. D. N.; Chantrasagul, C.; Manasboonpermpool, R.; Sathianvichitr, K.; Sangsre, P.; Surachatkumtonekul, T..

2022 IEEE Region 10 International Conference, TENCON 2022 ; 2022-November, 2022.

Article in English | Scopus | ID: covidwho-2192085

ABSTRACT

ABSTRACT

Amblyopia is a noteworthy disease in children leading to visual loss. This work focuses on creating a deep learning model for the detection of Amblyopia factors in patients wearing masks under the COVID-19 pandemic. © 2022 IEEE.

Keywords

Amblyopia; Convolutional neural network; Deep learning; Mask R-CNN; MTCNN; Red reflex; Anomaly detection; Learning approach; Learning models; Visual loss; Convolutional neural networks

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2022 IEEE Region 10 International Conference, TENCON 2022 Year: 2022 Document Type: Article

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