論文筆記（3）：Blessing of Dimensionality: High-dimensionality Feature and Its Efficient Compression
論文：Blessing of Dimensionality: High-dimensionality Feature and Its Efficient Compression for Face Verification 本文提出了高維度的特徵有利於性能提高的觀點。利用增長人臉特徵點提取的數量，和採樣多尺度圖像金字塔，來對傳統人臉特徵（LBP, Gabor, HOG, SIFT）實現高維度版本。實
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相關文章
- 1. 論文筆記（3）：Blessing of Dimensionality: High-dimensionality Feature and Its Efficient Compression
- 2. 【論文筆記】SafeHidden: An Efficient and Secure Information
- 3. 論文筆記 [3] CNN去compression artifacts
- 4. 《EfficientDet：Scalable and Efficient Object Detection》論文筆記
- 5. 論文筆記《Deep Compression》
- 6. 【Learning both Weights and Connections for Efficient Neural Networks】論文筆記
- 7. Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data 論文閱讀筆記
- 8. 論文筆記：Efficient Graph-Based Image Segmentation
- 9. 【Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huff】論文筆記
- 10. 閱讀筆記：《Computationally Efficient Neural Image Compression》