Adversarial learning for semi-supervised semantic segmentation
GAN生成對抗網絡：由兩個子網絡組成，generator和discriminator,在訓練過程中，這兩個子網絡進行着最小最大值機制，generator用隨機向量輸出一個目標數據分佈的樣例，discriminator從目標樣例中區分出生成器生成的樣例。generator通過後向傳播混淆discriminator，依此generator生成與目標樣例相似的樣例。 這篇論文中，將generator換成
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相關文章
- 1. 論文：Adversarial Learning for Semi-Supervised Semantic Segmentation
- 2. 《Learning Dynamic Routing for Semantic Segmentation》
- 3. Learning Deconvolution Network for Semantic Segmentation
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- 6. Improving Lesion Segmentation for Diabetic Retinopathy using Adversarial Learning
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- 8. Learning to Adapt Structured Output Space for Semantic Segmentation
- 9. Adversarial learning with multi-scale loss for skin lesion segmentation
- 10. [ACL2017]Adversarial Multi-Criteria Learning for Chinese Word Segmentation