most citedA comparative study of generative adversarial networks for image recognition algorithms based on deep learning and traditional methods

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eess.IV2024★ 1 cited

Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis

Junliang Du, Yiru Cang, Tong Zhou +2

This study introduces the Hybrid Multi-modal VGG (HM-VGG) model, a cutting-edge deep learning approach for the early diagnosis of glaucoma. The HM-VGG model utilizes an attention m…

eess.IV2024

Axial Attention Transformer Networks: A New Frontier in Breast Cancer Detection

Weijie He, Runyuan Bao, Yiru Cang +3

This paper delves into the challenges and advancements in the field of medical image segmentation, particularly focusing on breast cancer diagnosis. The authors propose a novel Tra…

eess.IV2024

Convolutional Neural Networks for Predictive Modeling of Lung Disease

Yingbin Liang, Xiqing Liu, Haohao Xia +3

In this paper, Pro-HRnet-CNN, an innovative model combining HRNet and void-convolution techniques, is proposed for disease prediction under lung imaging. Through the experimental c…