most citedA Lightweight GAN-Based Image Fusion Algorithm for Visible and Infrared Images

2 citations · 3 across the 5 of their papers we have counts for

collaborators

7 papers

eess.IV20242 cited

A Lightweight GAN-Based Image Fusion Algorithm for Visible and Infrared Images

Zhizhong Wu, Jiajing Chen, LiangHao Tan +3

This paper presents a lightweight image fusion algorithm specifically designed for merging visible light and infrared images, with an emphasis on balancing performance and efficien…

cs.LG2024

Reducing Bias in Deep Learning Optimization: The RSGDM Approach

Honglin Qin, Hongye Zheng, Bingxing Wang +3

Currently, widely used first-order deep learning optimizers include non-adaptive learning rate optimizers and adaptive learning rate optimizers. The former is represented by SGDM (…

cs.LG20241 cited

Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Function

Hongye Zheng, Bingxing Wang, Minheng Xiao +3

Adaptive optimizers are pivotal in guiding the weight updates of deep neural networks, yet they often face challenges such as poor generalization and oscillation issues. To counter…

cs.LG2024

Dynamic Hypergraph-Enhanced Prediction of Sequential Medical Visits

Wangying Yang, Zitao Zheng, Zhizhong Wu +2

This study introduces a pioneering Dynamic Hypergraph Networks (DHCE) model designed to predict future medical diagnoses from electronic health records with enhanced accuracy. The…

cs.AI2024

Multiple Greedy Quasi-Newton Methods for Saddle Point Problems

Minheng Xiao, Zhizhong Wu

This paper introduces the Multiple Greedy Quasi-Newton (MGSR1-SP) method, a novel approach to solving strongly-convex-strongly-concave (SCSC) saddle point problems. Our method enha…

cs.CV2024

Research on Image Super-Resolution Reconstruction Mechanism based on Convolutional Neural Network

Hao Yan, Zixiang Wang, Zhengjia Xu +3

Super-resolution reconstruction techniques entail the utilization of software algorithms to transform one or more sets of low-resolution images captured from the same scene into hi…