Self-supervised multi-task representation learning for sequential medical images
Self-supervised representation learning has achieved promising results for downstream visual tasks in natural images. However, its use in the medical domain, where there is an underlying anatomical structural similarity, remains underexplored. To address this shortcoming, we propose a self-supervise...
المؤلفون الرئيسيون: | Dong, N, Kampffmeyer, M, Voiculescu, I |
---|---|
التنسيق: | Conference item |
اللغة: | English |
منشور في: |
Springer
2021
|
مواد مشابهة
-
Federated partially supervised learning with limited decentralized medical images
حسب: Dong, N, وآخرون
منشور في: (2022) -
Towards robust partially supervised multi-structure medical image segmentation on small-scale data
حسب: Dong, N, وآخرون
منشور في: (2021) -
Learning underrepresented classes from decentralized partially labeled medical images
حسب: Dong, N, وآخرون
منشور في: (2022) -
Multi-task self-supervised visual learning
حسب: Doersch, C, وآخرون
منشور في: (2017) -
Self-Supervised Learning for Invariant Representations From Multi-Spectral and SAR Images
حسب: Pallavi Jain, وآخرون
منشور في: (2022-01-01)