141 citations · 249 across the 17 of their papers we have counts for
6 papers · 1 filter
A Teacher-Student Framework with Fourier Augmentation for COVID-19 Infection Segmentation in CT Images
Han Chen, Yifan Jiang, Hanseok Ko +1
Automatic segmentation of infected regions in computed tomography (CT) images is necessary for the initial diagnosis of COVID-19. Deep-learning-based methods have the potential to…
CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects
Ange Lou, Shuyue Guan, Hanseok Ko +1
Segmenting medical images accurately and reliably is important for disease diagnosis and treatment. It is a challenging task because of the wide variety of objects' sizes, shapes,…
A Distance-based Separability Measure for Internal Cluster Validation
Shuyue Guan, Murray Loew
To evaluate clustering results is a significant part of cluster analysis. Since there are no true class labels for clustering in typical unsupervised learning, many internal cluste…
CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation
Ange Lou, Shuyue Guan, Murray Loew
Currently, developments of deep learning techniques are providing instrumental to identify, classify, and quantify patterns in medical images. Segmentation is one of the important…
CFPNet: Channel-wise Feature Pyramid for Real-Time Semantic Segmentation
Ange Lou, Murray Loew
Real-time semantic segmentation is playing a more important role in computer vision, due to the growing demand for mobile devices and autonomous driving. Therefore, it is very impo…
Understanding the Ability of Deep Neural Networks to Count Connected Components in Images
Shuyue Guan, Murray Loew
Humans can count very fast by subitizing, but slow substantially as the number of objects increases. Previous studies have shown a trained deep neural network (DNN) detector can co…