13 papers
Contrastive and Variational Approaches in Self-Supervised Learning for Complex Data Mining
Yingbin Liang, Lu Dai, Shuo Shi +3
Complex data mining has wide application value in many fields, especially in the feature extraction and classification tasks of unlabeled data. This paper proposes an algorithm bas…
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…
Multi-Scale Transformer Architecture for Accurate Medical Image Classification
Jiacheng Hu, Yanlin Xiang, Yang Lin +3
This study introduces an AI-driven skin lesion classification algorithm built on an enhanced Transformer architecture, addressing the challenges of accuracy and robustness in medic…
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…