The u-net architecture achieves very good performance on very different biomedical segmentation applications.
Thanks to data augmentation with elastic deformations, it only needs very few annotated images and has a very reasonable training time of only 10 hours on a NVidia Titan GPU (6 GB).
可以在GPU訓練 10 小時。
We provide the full Caffe-based implementation and the trained network. We are sure that the u-net architecture can be applied easily to many more tasks.
提供了基於 caffe 實踐的開源程式碼，可以輕鬆實現。