20 papers
A Deep Learning Framework for Boundary-Aware Semantic Segmentation
Tai An, Weiqiang Huang, Da Xu +3
As a fundamental task in computer vision, semantic segmentation is widely applied in fields such as autonomous driving, remote sensing image analysis, and medical image processing.…
Adaptive Transformer Attention and Multi-Scale Fusion for Spine 3D Segmentation
Yanlin Xiang, Qingyuan He, Ting Xu +3
This study proposes a 3D semantic segmentation method for the spine based on the improved SwinUNETR to improve segmentation accuracy and robustness. Aiming at the complex anatomica…
A Hybrid CNN-Transformer Model for Heart Disease Prediction Using Life History Data
Ran Hao, Yanlin Xiang, Junliang Du +3
This study proposed a hybrid model of a convolutional neural network (CNN) and a Transformer to predict and diagnose heart disease. Based on CNN's strength in detecting local featu…
A Deep Learning Approach to Interface Color Quality Assessment in HCI
Shixiao Wang, Runsheng Zhang, Junliang Du +2
In this paper, a quantitative evaluation model for the color quality of human-computer interaction interfaces is proposed by combining deep convolutional neural networks (CNN). By…
Contrastive Learning for Cold Start Recommendation with Adaptive Feature Fusion
Jiacheng Hu, Tai An, Zidong Yu +2
This paper proposes a cold start recommendation model that integrates contrastive learning, aiming to solve the problem of performance degradation of recommendation systems in cold…
A Structured Reasoning Framework for Unbalanced Data Classification Using Probabilistic Models
Junliang Du, Shiyu Dou, Bohuan Yang +2
This paper studies a Markov network model for unbalanced data, aiming to solve the problems of classification bias and insufficient minority class recognition ability of traditiona…