research
∙
09/07/2023
A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ Segmentation
Although deep learning have revolutionized abdominal multi-organ segment...
share
research
∙
08/30/2023
SAM-Med2D
The Segment Anything Model (SAM) represents a state-of-the-art research ...
research
∙
04/13/2023
STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training
Large-scale models pre-trained on large-scale datasets have profoundly a...
research
∙
03/10/2023
Generative Model Based Noise Robust Training for Unsupervised Domain Adaptation
Target domain pseudo-labelling has shown effectiveness in unsupervised d...
research
∙
03/08/2023
FCN+: Global Receptive Convolution Makes FCN Great Again
Fully convolutional network (FCN) is a seminal work for semantic segment...
research
∙
11/17/2022
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation
Traffic flow analysis is revolutionising traffic management. Qualifying ...
research
∙
11/17/2022
NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning
Semi-Supervised Learning (SSL) aims to learn a model using a tiny labele...
research
∙
10/14/2022
Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT Scans
Tumor lesion segmentation is one of the most important tasks in medical ...
research
∙
10/04/2022
Robust Target Training for Multi-Source Domain Adaptation
Given multiple labeled source domains and a single target domain, most e...
research
∙
09/06/2022
An evaluation of U-Net in Renal Structure Segmentation
Renal structure segmentation from computed tomography angiography (CTA) ...
research
∙
03/09/2022
Dynamic Instance Domain Adaptation
Most existing studies on unsupervised domain adaptation (UDA) assume tha...
research
∙
11/06/2021
