RCNN學習筆記(1):Rich feature hierarchies for accurate object detection and semantic segmentation
rcnn主要做用就是用於物體檢測，就是首先經過selective search 選擇2000個候選區域，這些區域中有咱們須要的所對應的物體的bounding-box，而後對於每個region proposal 都wrap到固定的大小的scale,227*227(AlexNet Input),對於每個處理以後的圖片，把他都放到CNN上去進行特徵提取，獲得每一個region propo
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- 1. RCNN學習筆記(1):Rich feature hierarchies for accurate object detection and semantic segmentation
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- 4. Rich feature hierarchies for accurate object detection and semantic segmentation (RCNN)筆記
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- 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
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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