16 citations · 38 across the 8 of their papers we have counts for
10 papers
A Sneak Attack on Segmentation of Medical Images Using Deep Neural Network Classifiers
Shuyue Guan, Murray Loew
Instead of using current deep-learning segmentation models (like the UNet and variants), we approach the segmentation problem using trained Convolutional Neural Network (CNN) class…
A Novel Intrinsic Measure of Data Separability
Shuyue Guan, Murray Loew
In machine learning, the performance of a classifier depends on both the classifier model and the separability/complexity of datasets. To quantitatively measure the separability of…
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…
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…
Segmentation of Infrared Breast Images Using MultiResUnet Neural Network
Ange Lou, Shuyue Guan, Nada Kamona +1
Breast cancer is the second leading cause of death for women in the U.S. Early detection of breast cancer is key to higher survival rates of breast cancer patients. We are investig…