論文筆記《A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification》
這是博主自己讀論文的筆記哦，原文請在A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification下載~ 解決的問題： 皮膚病竈的分類與分割 模型設計的動機 分類與分割是兩個高度相關的任務，但是當前的研究往往只涉及到其中一個任務 分割可以幫助消除圖像中的干擾，提高分類準確性 特定類別的診斷
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相關文章
- 1. A MULTI-TASK FRAMEWORK WITH FEATURE PASSING MODULE FOR SKIN LESION CLASSIFICATION AND SEGMENTATION
- 2. 讀書筆記-多任務學習-A Novel Multi-task Deep Learning Model for Skin Lesion Segmentation and Classification
- 3. 論文筆記：A deep learning model integrating FCNNs and CRFs for brain tumor segmentation
- 4. Adversarial learning with multi-scale loss for skin lesion segmentation
- 5. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 論文筆記
- 6. 論文：Automated Vehicle Detection and Classification: Models, Methods, and Techniques翻譯（五）
- 7. 論文筆記：ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation
- 8. 【論文筆記】——FEATURE FUSION ENCODER DECODER NETWORK FOR AUTOMATIC LIVER LESION SEGMENTATION
- 9. 論文筆記《Automated melanoma recognition in dermoscopy images via very deep residual networks》
- 10. 論文筆記-DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification