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論文筆記:Rich feature hierarchies for accurate object detection and semantic segmentation
時間 2020-12-24
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Rich feature hierarchies for accurate object detection and semantic segmentation 概要 文章提出了一種目標檢測算法,使得平均準確度相較於目前的最優方法相對提升了30%。該方法使用了卷積神經網絡CNN來預測選取的區域從而定位和分割檢測目標。當標記的訓練數據較少時,該方法可以先在輔助數據集上進行有監督的預訓練,再到目標數據
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相關文章
1.
Rich feature hierarchies for accurate object detection and semantic segmentation
2.
【論文閱讀筆記】Rich feature hierarchies for accurate object detection and semantic segmentation
3.
論文:Rich feature hierarchies for accurate object detection and semantic segmentation 個人筆記
4.
論文筆記:Rich feature hierarchies for accurate object detection and semantic segmentation(R-CNN)
5.
論文學習《Rich feature hierarchies for accurate object detection and semantic segmentation》
6.
【論文閱讀】Rich feature hierarchies for accurate object detection and semantic segmentation
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R-CNN論文翻譯Rich feature hierarchies for accurate object detection and semantic segmentation
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【論文快讀】Rich feature hierarchies for accurate object detection and semantic segmentation
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Rich feature hierarchies for accurate object detection and semantic segmentation論文細讀
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