CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes2018—論文筆記
本論文來自CVPR2018， 讀於20190409。 Abstract 我們提出的Congested Scene Recognition（CSRNet）包含了兩個部分，一個是獲得二維特徵的前端，一個是使用膨脹CNN（dilated CNN）的後端。 我們在最常用的那四個數據集（(ShanghaiTech dataset, the UCF CC 50 dataset, the WorldEXPO’1
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相關文章
- 1. Summary - CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly
- 2. CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
- 3. 人羣密度估計--CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
- 4. 經典論文閱讀--CSRNet
- 5. [轉] Understanding Convolutional Neural Networks for NLP
- 6. Understanding Convolutional Neural Networks for NLP
- 7. Learning Convolutional Neural Networks for Graphs論文筆記
- 8. 【Fast Algorithms for Convolutional Neural Networks】論文筆記
- 9. 論文筆記《DermaKNet: Incorporating the knowledge of dermatologists to Convolutional Neural Networks for 》
- 10. Understanding Neural Networks Through Deep Visualization 論文筆記