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hzzhoulifeng
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add r-fcn paper notes
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README.md

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@@ -72,6 +72,11 @@ Reducing Internal Covariate Shift](https://github.com/fanOfJava/myblob/blob/mast
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-本文提出的模型(model)在不同的数据集上,如 PASCAL VOC、MS COCO、ILSVRC, 都进行了测试。在检测时间(timing)、检测精度(accuracy)上,均与目前物体检测领域 state-of-art 的检测方法进行了比较。
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详见[Paper Notes](http://blog.csdn.net/u010167269/article/details/52563573)
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5. [R-FCN: Object Detection via Region-based Fully Convolutional Networks](https://github.com/fanOfJava/myblob/blob/master/papers/object%20detection/R-FCN.pdf)
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这篇论文是NIPS 2016的一篇论文,主要贡献在于解决了“分类网络的位置不敏感性(translation-invariance in image classification)”与“检测网络的位置敏感性(translation-variance in object detection)”之间的矛盾,在提升精度的同时利用“位置敏感得分图(position-sensitive score maps)”提升了检测速度。
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详见[Paper Notes](https://zhuanlan.zhihu.com/p/30867916)
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