Abstract is missing.
- Automated Detection of Myopic Maculopathy in MMAC 2023: Achievements in Classification, Segmentation, and Spherical Equivalent PredictionYihao Li, Philippe Zhang, Yubo Tan, Jing Zhang, Zhihan Wang, Weili Jiang, Pierre-Henri Conze, Mathieu Lamard, Gwenolé Quellec, Mostafa El Habib Daho. 1-17 [doi]
- Swin-MMC: Swin-Based Model for Myopic Maculopathy Classification in Fundus ImagesLi Lu, Xuhao Pan, Panji Jin, Ye Ding. 18-30 [doi]
- Towards Label-Efficient Deep Learning for Myopic Maculopathy ClassificationJunlin Hou, Jilan Xu, Fan Xiao, Bo Zhang, Yiqian Xu, Yuejie Zhang, Haidong Zou, Rui Feng. 31-45 [doi]
- Ensemble Deep Learning Approaches for Myopic Maculopathy Plus Lesions SegmentationFan Xiao, Junlin Hou, Jilan Xu, Yiqian Xu, Bo Zhang, Yuejie Zhang, Haidong Zou, Rui Feng. 46-55 [doi]
- Beyond MobileNet: An Improved MobileNet for Retinal DiseasesWenhui Zhu, Peijie Qiu, Xiwen Chen, Huayu Li, Hao Wang, Natasha Leporé, Oana M. Dumitrascu, Yalin Wang 0001. 56-65 [doi]
- Prediction of Spherical Equivalent with Vanilla ResNetHuayu Li, Wenhui Zhu, Xiwen Chen, Yalin Wang 0001. 66-74 [doi]
- Semi-supervised Learning for Myopic Maculopathy AnalysisJónathan Heras. 75-82 [doi]
- A Clinically Guided Approach for Training Deep Neural Networks for Myopic Maculopathy ClassificationFabian Yii. 83-94 [doi]
- Classification of Myopic Maculopathy Images with Self-supervised Driven Multiple Instance Learning NetworkJiawen Li, Jaehyeon Soon, Qilai Zhang, Qifan Zhang, Yonghong He. 95-105 [doi]
- Self-supervised Learning and Data Diversity Based Prediction of Spherical EquivalentDi Liu, Li Wei, Bo Yang. 106-112 [doi]
- Myopic Maculopathy Analysis Using Multi-task Learning and Pseudo LabelingHyeonmin Kim, Hyeonseob Nam. 113-119 [doi]