Assisted Excitation of Activations: A Learning Technique to Improve Object Detect
CVPR2019 很簡單的一篇文章，不是在網絡結構設計或者loss上做改進， 而是提出一種簡單的學習策略。它基於curriculum learning 的思想：如果我們先學習簡單的任務， 再學習複雜的任務， 我們會取得更好的效果。 以YOLO爲例： 在YOLO的網絡中加入這樣的輔助激發層(AE）。 它根據ground truth的位置， 在原有特徵圖上激發對應位置（實質也是attention）。E
相關文章
- 1. Assisted Excitation of Activations:A Learning Technique to Improve Object Detectors論文解讀
- 2. CVPR 2007 Learning to detect a salient object
- 3. How To Improve Deep Learning Performance
- 4. [論文筆記] - PARTICULAR OBJECT RETRIEVAL WITH INTEGRAL MAX-POOLING OF CNN ACTIVATIONS
- 5. 2020-10-03 Object detect
- 6. Using AJAX to Improve the Bandwidth Performance of Web Applications
- 7. Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer(閱讀報告)
- 8. Reading Note: Detect to Track and Track to Detect
- 9. Vulnerability Extrapolation: Assisted Discovery of Vulnerabilities using Machine Learning
- 10. A journey of English learning three
- 更多相關文章...
- • XSL-FO instream-foreign-object 對象 - XSL-FO 教程
- • XSLT
- • 爲了進字節跳動，我精選了29道Java經典算法題，帶詳細講解
- • 使用Rxjava計算圓周率
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. Assisted Excitation of Activations:A Learning Technique to Improve Object Detectors論文解讀
- 2. CVPR 2007 Learning to detect a salient object
- 3. How To Improve Deep Learning Performance
- 4. [論文筆記] - PARTICULAR OBJECT RETRIEVAL WITH INTEGRAL MAX-POOLING OF CNN ACTIVATIONS
- 5. 2020-10-03 Object detect
- 6. Using AJAX to Improve the Bandwidth Performance of Web Applications
- 7. Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer(閱讀報告)
- 8. Reading Note: Detect to Track and Track to Detect
- 9. Vulnerability Extrapolation: Assisted Discovery of Vulnerabilities using Machine Learning
- 10. A journey of English learning three