Weakly Supervised Learning of Object-Part Attention Model for Fine-Grained Image Classification

时间 2020-12-25

标签 #细粒度弱监督繁體版

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Weakly Supervised Learning of Object-Part Attention Model for Fine-Grained Image Classification abstract：本文作者提出了一种弱监督的方法，它只需要图像级的标签来进行细粒度的分类。 1.introduction 有的两个物种的差别特别小，只有特别专业的人才能鉴别出来，关键是找到两个的鉴别区。如果

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1. 17-WILDCAT-Weakly-Supervised-Learning-of-DeepConvNets
2. 【论文总结】weakly- and semi-supervised learning of a DCNN for semantic Image Segmentation
3. Thinking in Weakly Supervised Learning
4. Residual attention network for image classification
5. Residual Attention Network for Image Classification
6. Two-Phase Learning for Weakly Supervised Object Localization
7. Learning Pixel-level segmantic affinity with image-level supervision for weakly supervised segmentat
8. Deep Self-Taught Learning for Weakly Supervised Object Localization
9. 论文笔记：Areas of Attention for Image Captioning
10. 《Deep Self-Taught Learning for Weakly Supervised Object Localization》

>>更多相关文章<<