《Deep Active Learning for Axon-Myelin Segmentation on Histology Data》--閱讀筆記-Arxiv

時間 2021-01-02

標籤 active learning MCDropout 简体版

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Active learning的核心是選擇most informative的sample，這個策略是有創新型的（https://github.com/neuropoly/deep-active-learning） Authors M´elanie Lubrano di Scandalea, Christian S. Perone, Mathieu Boudreau, Julien Cohen

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1. 《A sparse annotation strategy based on attention-guided active learning for 3D medic》--閱讀筆記-Arxiv
2. 閱讀論文：Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
3. Deep Watershed Transform for Instance Segmentation閱讀筆記
4. A Review on Deep Learning Techniques Applied to Semantic Segmentation 閱讀筆記
5. 論文閱讀筆記《Deep Active Learning for Civil Infrastructure Defect Detection and Classification》
6. 論文閱讀筆記《Segmentation-based deep-learning approach for surface-defect detection》
7. 【論文閱讀筆記】PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
8. 論文閱讀：PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
9. Deep Residual Learning for Image Recognition閱讀筆記
10. Deep Reinforcement Learning for Dialogue Generation閱讀筆記

>>更多相關文章<<