Deep transfer learning has emerged as a powerful paradigm in image classification, enabling models to leverage knowledge acquired from large, labelled datasets to perform effectively on new tasks with ...

Deep learning has transformed flower image classification by replacing hand-crafted features with end-to-end trainable models capable of capturing complex visual patterns. Convolutional neural ...

A comprehensive two-stage deep learning framework for kidney tumor subtype classification from CT imaging, featuring contrast enhancement techniques and achieving state-of-the-art performance.

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...

ABSTRACT: This study proposes a multimodal AI model for classifying Vietnamese digital learning materials by integrating three key information sources: text content, image and graphic features, and ...

White Blood Cell Classification is a deep learning project built with Python, TensorFlow, and Keras that classifies five types of WBCs from microscopic images using a CNN model. With advanced image ...

Abstract: With the rapid development of computer vision technology, image classification algorithm based on deep learning has become a hot research and application field. At present, the mainstream ...

The Tapenade pipeline enables single-cell, whole-mount 3D quantification in dense multilayer organoids, linking spatial gene co-expression and nuclear deformation to emerging tissue-scale organization ...