【Auto ML】《DetNAS: Backbone Search for Object Detection》閱讀分享
Paper Reading Note Paper URL：link Code:link TL;DR 文章利用single path搜索框架的拓展性，首次提出搜索檢測器backbone的方法，過程包括imagenet的預訓練，coco上的finetune，進化算法的子模型搜索。整個算法步驟很清晰，結果也不錯, 搜出來的backbone在COCO超過超過resnet50,resnet101,且計算量更
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相關文章
- 1. 論文閱讀：Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection
- 2. Selective Search for Object Recognition(閱讀)
- 3. DetNet: A Backbone network for Object Detection
- 4. DetNet：A Backbone network for Object Detection
- 5. [論文閱讀]CBNet|A Novel Composite Backbone Network Architecture for Object Detection
- 6. DetNet: A Backbone network for Object Detection論文閱讀記錄
- 7. Feature Pyramid Networks for Object Detection 閱讀筆記
- 8. 論文閱讀-《Focal Loss for Dense Object Detection》
- 9. 翻譯：Selective Search for Object Detection
- 10. 論文閱讀：EfficientDet: Scalable and Efficient Object Detection