[解讀] Deep Clustering for Unsupervised Learning of Visual Features
鏈接: https://arxiv.org/abs/1807.05520v2 本文通過在傳統的卷積網絡中嵌入 k 均值聚類算法, 得到僞標籤, 實現無監督的視覺特徵學習, 也是一種自監督學習. 相關的工作 有不少無監督特徵學習方法, 例如 [10] 中也使用了 k 均值聚類來預訓練卷積網絡, 但訓練是逐層進行的, 而不是端到端的. 在 [3,16,35,66,68] 中也通過學習卷積特徵進行圖像聚
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相關文章
- 1. Deep Clustering for Unspervised Learning of Visual Features
- 2. Deep Temporal Clustering: Fully unsupervised learning of time-domain features
- 3. [短]粗讀CVPR2019論文 Deep Multimodal Clustering for Unsupervised Audiovisual Learning
- 4. Unsupervised Deep Embedding for Clustering Analysis(DEC)
- 5. Clustering - Unsupervised learning introduction
- 6. 《A Review of Unsupervised Feature Learning and Deep Learning for Time-Series Modeling》筆記
- 7. Deep Unsupervised Clustering Using Mixture of Autoencoders(MIXAE)
- 8. Unsupervised Subtyping of Cholangiocarcinoma Using a Deep Clustering Convolutional Autoencoder
- 9. 論文閱讀-《Learning Deep Features for Discriminative Localization》
- 10. Deep Unsupervised Clustering Using Mixture of Autoencoders(2017)