Learning Self-Supervised Representations for Label Efficient Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus Images-Reference-Cited by-同舟云学术

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Learning Self-Supervised Representations for Label Efficient Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus Images

Published:2023-06-18 Issue: Volume: Page:
ISSN:
Container-title:2023 International Joint Conference on Neural Networks (IJCNN)
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Author:

Gupta Ekta¹,Gupta Varun¹,Chopra Muskaan¹,Chhipa Prakash Chandra²,Liwicki Marcus²

Affiliation:

1. Chandigarh College of Engineering and Technology, Punjab University,Chandigarh,India

2. Machine Learning Group, Luleå Tekniska Universitet,EISLAB,Luleå,Sweden

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10190990/10190992/10191796.pdf?arnumber=10191796

Reference37 articles.

1. A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning

2. Longitudinal self-supervised learning

3. Convolutional neural networks based transfer learning for diabetic retinopathy fundus image classification

4. Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images

5. Developing intelligent medical image modality classification system using deep transfer learning and LDA;hassan;Sci Rep,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Source-free active domain adaptation for diabetic retinopathy grading based on ultra-wide-field fundus images;Computers in Biology and Medicine;2024-05

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