RCNN學習筆記(1):Rich feature hierarchies for accurate object detection and semantic segmentation
rcnn主要作用就是用於物體檢測，就是首先通過selective search 選擇2000個候選區域，這些區域中有我們需要的所對應的物體的bounding-box，然後對於每一個region proposal 都wrap到固定的大小的scale,227*227(AlexNet Input),對於每一個處理之後的圖片，把他都放到CNN上去進行特徵提取，得到每個region proposal的f
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相關文章
- 1. RCNN學習筆記(1):Rich feature hierarchies for accurate object detection and semantic segmentation
- 2. Rich feature hierarchies for accurate object detection and semantic segmentation
- 3. RCNN：Rich feature hierarchies for accurate object detection and semantic segmentation
- 4. Rich feature hierarchies for accurate object detection and semantic segmentation (RCNN)筆記
- 5. RCNN學習筆記（1）-RCNN-Rich feature hierarchies for accurate object detection and semantic segmentation論文
- 6. [RCNN]Rich feature hierarchies for accurate object detection and semantic segmentation
- 7. 【目標檢測】RCNN (Rich feature hierarchies for accurate object detection and semantic segmentation)
- 8. 【RCNN】《Rich feature hierarchies for accurate object detection and semantic segmentation 》
- 9. 論文筆記：Rich feature hierarchies for accurate object detection and semantic segmentation
- 10. 【論文閱讀筆記】Rich feature hierarchies for accurate object detection and semantic segmentation