Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...
📋 Project Overview This project presents a novel CBAM-guided channel pruning framework for efficient osteoporosis classification using knee X-ray images. The methodology achieves 55.9% parameter ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...
Abstract: Deep learning models have shown impressive performance across a range of computer vision tasks. However, their lack of transparency limits their adoption in tasks where a clear understanding ...
Google AI has just unveiled Gemini 2.5 Flash Image, a new generation image model designed to let users generate and edit images simply by describing them—and its true innovation is how it delivers ...
This study aimed to develop a hybrid deep learning model for classifying multiple fundus diseases using ultra-widefield (UWF) images, thereby improving diagnostic efficiency and accuracy while ...
Abstract: The use of deep learning (DL) in medical image analysis has significantly improved the ability to predict lung cancer. In this study, we introduce a novel deep convolutional neural network ...
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