【目標檢測】[論文閱讀][yolo] You Only Look Once: Unified, Real-Time Object Detection
論文名稱《You Only Look Once: Unified, Real-Time Object Detection》html 摘要 一、以前的目標檢測方法採用目標分類思想解決檢測問題，本文提出一個基於迴歸的框架，用於目標的定位及識別。
二、一個網絡，一次預測便可得到目標的檢測框（bounding boxs）和 類別機率。
三、所提目標檢測框架運算速度很是快。基本YOLO 模型45幀/S。簡化
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相關文章
- 1. YOLO論文閱讀 ⽬標檢測： You Only Look Once: Unified, Real-Time Object Detection 2018.12.20
- 2. 論文閱讀筆記：You Only Look Once: Unified, Real-Time Object Detection(YOLO)
- 3. You Only Look Once Unified, Real-Time Object Detection
- 4. 【目標檢測】YOLO論文詳解（You Only Look Once: Unified, Real-Time Object Detection）
- 5. You Only Look Once: Unified, Real-Time Object Detection
- 6. YOLOv1：You Only Look Once: Unified, Real-Time Object Detection
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- 8. 【目標檢測】YOLO: You Only Look Once
- 9. 【論文閱讀】YOLOv1-You Only Look Once: Unified, Real-Time Object Detection Joseph
- 10. 論文閱讀筆記：You Only Look Once: Unified, Real-Time Object Detection