MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching
MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching 摘要：由於在學習特徵表示和學習特徵比較函數的成功，我們提出了一種統一的方法來結合訓練塊匹配系統。我們的系統成爲MatchNet，由深度卷積網絡組成從塊來提取特徵，和三個全連接層的網絡來計算提取特徵的相似性。爲了確保實驗可重複性，我們在標準數據集
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相關文章
- 1. 001: MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching
- 2. 《Learning Semantic Concepts and Order for Image and Sentence Matching》
- 3. Unifying Task-oriented Knowledge Graph Learning and Recommendation
- 4. DIVERSITY REGULARIZED METRIC LEARNING FOR PERSON RE-IDENTIFICATION（ICIP2016）
- 5. Similarity Metric Learning for Face Recognition2013
- 6. Ranked List Loss for Deep Metric Learning
- 7. 2D3D-MatchNet: Learning to Match Keypoints Across 2D Image and 3D Point Cloud
- 8. Matching Networks for one Shot Learning 閱讀筆記
- 9. Survey and experimental study on metric learning methods
- 10. Learning Semantic Concepts and Order for Image and Sentence Matching筆記