使用卷积神经网络进行斜视分类

2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2021-04-13 DOI:10.1109/ICAIIC51459.2021.9415280

Donghwan Kim, Jaehan Joo, Guohua Zhu, Jeongbin Seo, Jaeseung Ha, S. Kim

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引用次数: 1

摘要

早期诊断和治疗弱视，包括斜视，对于防止婴幼儿永久性失明非常重要。在本文中，我们设计了一个卷积神经网络来对外斜视、内斜视和正常眼睛进行分类。所设计的模型以9张照片的前视图作为输入数据，并根据训练epoch的个数，使用预测精度来评价模型的性能。

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Strabismus Classification using Convolutional Neural Networks

Early diagnosis and treatment of amblyopia, including strabismus, is important to prevent permanent blindness in infants and toddlers. In this paper, we design an convolutional neural networks that classifies exotropia, esotropia, and normal eyes. Designed model uses the front view of 9-photo as input data, and evaluates its performance using prediction accuracy according to the number of training epochs.

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2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

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