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Unet++: A nested U-Net architecture for medical image segmentation
Unet++: A nested U-Net architecture for medical image segmentation. -
Fluid Dynamics Dataset
The dataset used for testing the U-Net and U-Net-MG models for flow past a stationary cylinder, flow past two cylinders in out-of-phase motion, and flow past an oscillating foil. -
U-Net neural networks for the segmentation of living cells
The dataset employed in this study were acquired in the BCS Lab and consists of microscope images of an experiment using a microfluidic device. -
Automatic Skull Stripping of Rat and Mouse Brain MRI Data Using U-Net
A dataset of mouse brain MRI images for automatic skull stripping and segmentation using U-Net architecture. -
MDU-Net: Multi-scale Densely Connected U-Net for Biomedical Image Segmentation
Biomedical image segmentation plays a central role in quantitative analysis, clinical diagnosis, and medical intervention. -
Automatic Architecture Search for Image Translator
Image translators have been successfully applied to many important low level image processing tasks. However, classical network architecture of image translator like U-Net, is... -
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segme...
The V-Net is a deep learning model for medical image segmentation that uses a U-Net architecture. -
3D Unet: A Deep Learning Model for Medical Image Segmentation
The 3D Unet is a deep learning model for medical image segmentation that uses a U-Net architecture. -
R2U-Net: A Deep Learning Model for Medical Image Segmentation
The R2U-Net is a deep learning model for medical image segmentation that combines U-Net, ResNet, and recurrent neural network (RCNN). -
Training a U-Net based on a random mode-coupling matrix to recover acoustic i...
A U-Net is trained to recover acoustic interference striations (AISs) from distorted ones. A random mode-coupling matrix model is introduced to generate a large number of... -
Medico Automatic Polyp Segmentation Challenge
Polyp segmentation using U-Net-ResNet50 -
Building Change Detection Using Multi-Temporal Airborne LiDAR Data
Building change detection using multi-temporal airborne LiDAR data -
Implementation of a Modified U-Net for Medical Image Segmentation on Edge Devices
Medical image segmentation on edge devices -
Fully Automatic Mitral Valve Extraction from 4D CT Images
A fully automatic mitral valve extraction method from input to output for all phases of 4D CT images. -
U-net: Convolutional networks for biomedical image segmentation
The U-net is a deep convolutional neural network for biomedical image segmentation. -
Comparison of 2D vs. 3D U-Net Organ Segmentation in abdominal 3D CT images
80 CT-scans and related label data found in various public sources were considered for training and testing of U-Net architectures.
