論文筆記：YOLOv4: Optimal Speed and Accuracy of Object Detection
中心思想： 在提出YOLOv4之前，作者先對現有的主流改進思路，進行了分類&綜述 基於上述的改進思路進行嘗試，整合，最終提出了YOLOv4。主要的貢獻在於： 能夠實現低成本的訓練（只用1張卡） 驗證了訓練&預測過程中的一些trick Bag of Freebies Bag of Freebies指的是通過更好的訓練方式來得到性能的提升，而這種訓練方式不會對模型的預測(inference)帶來比較大
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相關文章
- 1. YOLOv4::Optimal Speed and Accuracy of Object
- 2. YOLOv4: Optimal Speed and Accuracy of Object Detection 論文筆記
- 3. 《YOLOv4：Optimal Speed and Accuracy of Object Detection》論文筆記
- 4. 【論文閱讀筆記】Yolov4：Optimal Speed and Accuracy of Object Detection
- 5. YOLOv4: Optimal Speed and Accuracy of Object Detection
- 6. (2020.04) Review: YOLOv4: Optimal Speed and Accuracy of Object Detection
- 7. YOLOv4 Optimal Speed and Accuracy of Object Detection
- 8. 【論文學習記錄】YOLOv4: Optimal Speed and Accuracy of Object Detection
- 9. 【論文閱讀】YOLOv4: Optimal Speed and Accuracy of Object Detection
- 10. 論文閱讀：YOLOv4: Optimal Speed and Accuracy of Object Detection