Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutio
理解論文 Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutional Networks Abstract 1.基於概率label空間上的Wasserstein距離，提出了一種基於語義信息的dice分數多類分割方法。 2.我們提出了一個整體的CNN，
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相關文章
- 1. Dice Similarity Coefficent vs. IoU Dice係數和IoU
- 2. LEARNING VOLUMETRIC SEGMENTATION FOR LUNG TUMOR
- 3. Improving Lesion Segmentation for Diabetic Retinopathy using Adversarial Learning
- 4. Structured Knowledge Distillation for Semantic Segmentation
- 5. 【論文閱讀】Structured Knowledge Distillation for Semantic Segmentation
- 6. Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks
- 7. Imbalanced Data
- 8. Holistic Recognition of Low Quality License Plates by CNN using Track Annotated Data 翻譯
- 9. Dice Loss
- 10. 知識蒸餾學習筆記2--Structured Knowledge Distillation for Semantic Segmentation