論文閱讀——CcNet:A cross-connected convolutional network for segmenting retinal vessels using multi-scale
論文閱讀：CcNet:A cross-connected convolutional network for segmenting retinal vessels using multi-scale CcNet 時間：2019/5 視網膜血管分割有助於幫助診斷糖尿病視網膜病變。目前RVS的自動分割面臨着模型精度、魯棒性及分割速度的限制。本文提出了一種交叉連接的RVS分割網絡叫做CcNet。在CeN
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相關文章
- 1. 論文閱讀筆記：CcNet: A cross-connected convolutional network for segmenting retinal vessels using 多尺度特徵
- 2. 論文閱讀《Edge Detection Using Convolutional Neural Network》
- 3. 《Dual Encoding U-Net for Retinal Vessel Segmentation》閱讀筆記-MICCAI2019
- 4. 【論文閱讀】Learning Deconvolution Network for Semantic Segmentation
- 5. 論文閱讀《Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching》
- 6. PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization論文閱讀
- 7. 【論文閱讀筆記】ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
- 8. 論文閱讀筆記：ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
- 9. 論文閱讀（7）：VarGFaceNet: An Efficient Variable Group Convolutional Neural Network for Lightweight FR
- 10. 【論文閱讀】ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices