Continual Learning for Domain Adaptation in Chest X-ray ClassificationAxel SaalbachHeinrich SchulzMatthias Lenga
Domain Adaptation(part of Transfer Learning) Learning to Learn (Meta Learning) Online Learning(i.i.d data) Open World Learning(subset of continual learning)。 第三篇是“Class-incremental learning: survey and performance evaluation“,2020年10月28日发表: incremental learning,即递增学习,是可取的,1)...
including foundation models, domain adaptation, meta-learning, test-time adaptation, generative models, reinforcement learning and federated learning. 通过这样做,我们对遗忘进行了全面的检查,涵盖了更广泛的背景和应用。 在本次调查中,我们根据具体的应用场景,将机器学习中的遗忘分为两类:有害遗忘和有益遗忘。
[05] Gaze-directed Vision GNN for Mitigating Shortcut Learning in Medical Image 1948 -- 2:05 App [33] Intelligent Preoperative Diagnosis and Surgical Planning 612 -- 1:57 App [23] Self-supervised neural network-based endoscopic monocular 3D reconstruction 530 -- 2:02 App [11] Exploiting Geo...
Therefore, we apply joint positive and negative learning on both high- and low-quality samples to reduce the risk of using wrong information. We conduct extensive experiments that demonstrate the effectiveness of our proposed method for CTDA in the image domain, outperforming the state-of-the-art...
These efforts are particularly related to the concepts of “transfer learning” [159,160], “domain adaptation” [161–163], “adversarial training” [164–167] and “lifelong” or “continual learning” [168,169]. Even if non-i.i.d. issues are circumvented or simply do not occur, an ...
- Miccai Workshop on Domain Adaptation & Representation Transfer 被引量: 0发表: 2024年 PromptFusion: Decoupling Stability and Plasticity for Continual Learning Continual learning refers to the capability of continuously learning from a stream of data. Current research mainly focuses on relieving ...
Test-time adaptation (TTA) has been proven to effectively improve the adaptability of deep learning semantic segmentation models facing continuous changeab... Z Wang,Y Zhang,Z Zhang,... - 《Remote Sensing》 被引量: 0发表: 2024年 Pyrolusite surface transformations measured in real-time during th...
Ouyang. Mutual crf- gnn for few shot learning. In Proceedings of the IEEE Con- ference on Computer Vision and Pattern Recognition, 2021. 2 [50] S. Tang, P. Su, D. Chen, and W. Ouyang. Gradient regu- larized contrastive learning for continual domain adaptation. ...
On the other hand, Domain Adaptation methods [78], [79], [80] work with a distinct situation, close to Transfer Learning, and they are in general deployed in centralized frameworks. However, some works aligned with this line of research talk about Federated Transfer Learning [81], and consi...