《An Active Learning Approach for Reducing Annotation Cost in Skin Lesion Analysis》--閱讀筆記-MLMI
Authors Xueying Shi, Qi Dou, Cheng Xue, Jing Qin, Hao Chen, Pheng-Ann Heng 港中文王平安組是真的屌啊 Motivation 由於皮膚癌是人類最常見的惡性腫瘤之一，因此自動皮膚病變分析在臨牀實踐中非常重要。現有的方法與深度學習已經取得了顯着的緊張，但是，嚴重依賴於大規模標記數據集。文章目的是使用少量的數據，但是仍然取得SOTA
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相關文章
- 1. 《Cost-Effective Active Learning for Hierarchical Multi-Label Classification》--閱讀筆記-IJCAI
- 2. Adversarial learning with multi-scale loss for skin lesion segmentation
- 3. 論文筆記：Learning how to Active Learn: A Deep Reinforcement Learning Approach
- 4. 閱讀論文：Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
- 5. 論文閱讀筆記 Meta-Learning for Batch Mode Active Learning
- 6. 論文閱讀筆記（三十四）：An Analysis of Scale Invariance in Object Detection－SNIP
- 7. 《A sparse annotation strategy based on attention-guided active learning for 3D medic》--閱讀筆記-Arxiv
- 8. 論文閱讀筆記：Transfer Learning for Deep Sentiment Analysis
- 9. FeUdal Networks for Hierarchical Reinforcement Learning 閱讀筆記
- 10. 論文閱讀筆記《Active One-shot Learning》