| Record Type: |
Electronic resources
: Monograph/item
|
| Title/Author: |
Myopic maculopathy analysis/ edited by Bin Sheng, Hao Chen, Tien Yin Wong. |
| Reminder of title: |
MICCAI Challenge MMAC 2023, held in conjunction with MICCAI 2023, virtual event, October 8-12, 2023 : proceedings / |
| remainder title: |
MMAC 2023 |
| other author: |
Sheng, Bin. |
| corporate name: |
Myopic Maculopathy Analysis Challenge |
| Published: |
Cham :Springer Nature Switzerland : : 2024., |
| Description: |
x, 122 p. :ill., digital ;24 cm. |
| [NT 15003449]: |
Automated Detection of Myopic Maculopathy in MMAC 2023: Achievements in Classification, Segmentation, and Spherical Equivalent Prediction -- Swin-MMC: Swin-Based Model for Myopic Maculopathy Classification in Fundus Images -- Towards Label-efficient Deep Learning for Myopic Maculopathy Classification -- Ensemble Deep Learning Approaches for Myopic Maculopathy Plus Lesions Segmentation -- Beyond MobileNet: An improved MobileNet for Retinal Diseases -- Prediction of Spherical Equivalent With Vanilla ResNet -- Semi-supervised learning for Myopic Maculopathy Analysis -- A Clinically Guided Approach for Training Deep Neural Networks for Myopic Maculopathy Classification -- Classification of Myopic Maculopathy Images with Self-supervised Driven Multiple Instance Learning Network -- Self-supervised Learning and Data Diversity based Prediction of Spherical Equivalent -- Myopic Maculopathy Analysis using Multi-Task Learning and Pseudo Labeling. |
| Contained By: |
Springer Nature eBook |
| Subject: |
Eye - Diseases - |
| Online resource: |
https://doi.org/10.1007/978-3-031-54857-4 |
| ISBN: |
9783031548574 |