10 citations · 22 across the 18 of their papers we have counts for
8 papers · 1 filter
Quasi-supervised Learning for Super-resolution PET
Guangtong Yang, Chen Li, Yudong Yao +2
Low resolution of positron emission tomography (PET) limits its diagnostic performance. Deep learning has been successfully applied to achieve super-resolution PET. However, common…
Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature Representation
Tingting Shen, Junhang Li, Can Tong +4
Nonnegative matrix factorization (NMF) has been widely used to dimensionality reduction in machine learning. However, the traditional NMF does not properly handle outliers, so that…
CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron
Wanli Liu, Chen Li, Ning Xu +9
Cervical cancer is the seventh most common cancer among all the cancers worldwide and the fourth most common cancer among women. Cervical cytopathology image classification is an i…
Subspace Nonnegative Matrix Factorization for Feature Representation
Junhang Li, Jiao Wei, Can Tong +6
Traditional nonnegative matrix factorization (NMF) learns a new feature representation on the whole data space, which means treating all features equally. However, a subspace is of…
TOD-CNN: An Effective Convolutional Neural Network for Tiny Object Detection in Sperm Videos
Shuojia Zou, Chen Li, Hongzan Sun +6
The detection of tiny objects in microscopic videos is a problematic point, especially in large-scale experiments. For tiny objects (such as sperms) in microscopic videos, current…
Improving the Level of Autism Discrimination through GraphRNN Link Prediction
Haonan Sun, Qiang He, Shouliang Qi +2
Dataset is the key of deep learning in Autism disease research. However, due to the few quantity and heterogeneity of samples in current dataset, for example ABIDE (Autism Brain Im…