筆記——Learning Transferable Architectures for Scalable Image Recognition
主要思想： 通過NAS(Neural Architecture Search Framework)在CIFAR-10 dataset上找到最優的網絡結構，再擴展到ImageNet dataset上。 模型提升—— This paper 1.2%better computer cost: a reductionof 28% 定義優化問題： 定義兩種類型的convolution layer：
相關文章
- 1. Learning Transferable Architectures for Scalable image recognition
- 2. Learning Transferable Architectures for Scalable Image Recognition
- 3. Paper Reading:Learning Transferable Architectures for Scalable Image Recognition
- 4. 自學網絡結構（二）：Learning Transferable Architectures for Scalable Image Recognition
- 5. Deep Residual Learning for Image Recognition 筆記
- 6. 【論文筆記】Deep Residual Learning for Image Recognition
- 7. NASNet:Learning Transferable Architectures for Scalable Image Recognition 學習可伸縮的圖像識別的可轉移架構
- 8. Deep Residual Learning for Image Recognition閱讀筆記
- 9. Deep Residual Learning for Image Recognition筆記
- 10. Deep Residual Learning for Image Recognition 論文筆記
- 更多相關文章...
- • ASP.NET Razor - 標記 - ASP.NET 教程
- • RSS
元素 - RSS 教程 - • Tomcat學習筆記（史上最全tomcat學習筆記）
- • Java Agent入門實戰（三）-JVM Attach原理與使用
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。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. Learning Transferable Architectures for Scalable image recognition
- 2. Learning Transferable Architectures for Scalable Image Recognition
- 3. Paper Reading:Learning Transferable Architectures for Scalable Image Recognition
- 4. 自學網絡結構（二）：Learning Transferable Architectures for Scalable Image Recognition
- 5. Deep Residual Learning for Image Recognition 筆記
- 6. 【論文筆記】Deep Residual Learning for Image Recognition
- 7. NASNet:Learning Transferable Architectures for Scalable Image Recognition 學習可伸縮的圖像識別的可轉移架構
- 8. Deep Residual Learning for Image Recognition閱讀筆記
- 9. Deep Residual Learning for Image Recognition筆記
- 10. Deep Residual Learning for Image Recognition 論文筆記