論文筆記：Towards perspective-free object counting with deep learning
Towards perspective-free object counting with deep learning 概要 文章提出了一種精確估算交通擁堵環境下車輛數量或密集人羣中人數的模型。 組成部分： CountingCNN：迴歸模型，學習從圖像樣本到對應的目標密度圖的映射 HydraCNN：多規模的非線性迴歸模型，使用不同規模下的圖像樣本生成密度預測 具體方法 生成密度圖 對於訓練圖像中每
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相關文章
- 1. Towards perspective-free object counting with deep learning
- 2. 人車密度估計--Towards perspective-free object counting with deep learning
- 3. 論文筆記：《Playing Atari with Deep Reinforcement Learning》
- 4. Hierarchical Object Detection with Deep Reinforcement Learning論文筆記
- 5. Towards High Performance Video Object Detection論文筆記
- 6. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks論文筆記
- 7. Machine Learning & Deep Learning 論文閱讀筆記
- 8. 論文筆記：Deep Residual Learning
- 9. 論文筆記(1)：Deep Learning.
- 10. 論文筆記：Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering