361 citations · 419 across the 9 of their papers we have counts for
9 papers
UniMOS: A Universal Framework For Multi-Organ Segmentation Over Label-Constrained Datasets
Can Li, Sheng Shao, Junyi Qu +2
Machine learning models for medical images can help physicians diagnose and manage diseases. However, due to the fact that medical image annotation requires a great deal of manpowe…
Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Image Segmentation
Shuchao Pang, Anan Du, Mehmet A. Orgun +5
Automatic tumor or lesion segmentation is a crucial step in medical image analysis for computer-aided diagnosis. Although the existing methods based on Convolutional Neural Network…
Graph Learning based Recommender Systems: A Review
Shoujin Wang, Liang Hu, Yan Wang +6
Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS). GLRS employ advanced graph learning approaches to model u…
A Deep Framework for Cross-Domain and Cross-System Recommendations
Feng Zhu, Yan Wang, Chaochao Chen +3
Cross-Domain Recommendation (CDR) and Cross-System Recommendations (CSR) are two of the promising solutions to address the long-standing data sparsity problem in recommender system…
Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Images for Segmentation
Shuchao Pang, Anan Du, Mehmet A. Orgun +5
Automatic tumor segmentation is a crucial step in medical image analysis for computer-aided diagnosis. Although the existing methods based on convolutional neural networks (CNNs) h…
Graph Learning Approaches to Recommender Systems: A Review
Shoujin Wang, Liang Hu, Yan Wang +7
Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS). GLRS mainly employ the advanced graph learning approaches…