Abstract: This study investigates the utilization of a hybrid Convolutional Neural Network (CNN) and Vision Transformer (ViT) model, employing transfer learning methods, to enhance brain stroke ...
Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...
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 ...
Abstract: Remote sensing image captioning (RSIC) aims to generate accurate and concise textual descriptions for remote sensing (RS) images. It plays a significant role in the analysis of Earth ...
Introduction: Deep learning has significantly advanced medical image analysis, enabling precise feature extraction and pattern recognition. However, its application in computational material science ...
Transfer learning is a machine learning technique that allows a model trained on one task to be repurposed or fine-tuned for a related task, drastically reducing the amount of data and computational ...
Summary: AI models trained on MRI data can now distinguish brain tumors from healthy tissue with high accuracy, nearing human performance. Using convolutional neural networks and transfer learning ...
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