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There is large consent that successful training of deep networks requires many thousand annotated training samples.
In this paper, we propose a Recurrent Convolutional Neural Network (RCNN) based on U-Net as well as a Recurrent Residual Convolutional Neural Network (RRCNN) based on U-Net models, which are named RU-Net and R2U-Net respectively.
SOTA for Lung Nodule Segmentation on LUNA
Road extraction from aerial images has been a hot research topic in the field of remote sensing image analysis.
#2 best model for Retinal Vessel Segmentation on STARE (F1 score metric)
We propose iW-Net, a deep learning model that allows for both automatic and interactive segmentation of lung nodules in computed tomography images.