You Only Look Once: Unified, Real-Time Object Detection
Abstract 作者將目標檢測當作迴歸問題來處理，以此來解決目標檢測中的bbox定位和相關類別概率預測問題。同SOTA的檢測系統相比，YOLO在定位問題上出錯概率更大，而在背景預測的問題上，fpr顯著地更小。 1. Introduction 無論是在訓練還是在測試的時候，YOLO處理的水平都是在整張圖片上進行的，因此它很輕易地就可以對背景信息的類別和外表進行編碼。YOLO的泛化性非常強，即，在n
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相關文章
- 1. You Only Look Once: Unified, Real-Time Object Detection
- 2. You Only Look Once Unified, Real-Time Object Detection
- 3. 【YOLOv1】《You Only Look Once: Unified, Real-Time Object Detection》
- 4. YOLOv1：You Only Look Once: Unified, Real-Time Object Detection
- 5. you only look once
- 6. You Only Look Once: Unified, Real-Time Object Detection （YOLO 論文翻譯）
- 7. YoLo： You Only Look Once: Unified, Real-Time Object Detection譯文
- 8. You Only Look Once: Unified, Real-Time Object Detection閱讀筆記
- 9. YOLO(You Only Look Once):Real-Time Object Detection
- 10. 論文閱讀筆記：You Only Look Once: Unified, Real-Time Object Detection(YOLO)