AI learns to read ancient Japanese pottery with 93% accuracy

Classifying ancient pottery has always depended on the trained judgment of an archaeologist. Identifying the subtle ...
Scientific Research Publishing

A Lightweight MobileViT with a Dual-Path Attention Mechanism for MRI Image Classification ()

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...
The New York Times

Deep in China’s Mountains, a Nuclear Revival Takes Shape

In the lush, misty valleys of southwest China, satellite imagery reveals the country’s accelerating nuclear buildup, a force designed for a new age of superpower rivalry. One such valley is known as ...
Frontiers

Traditional machine learning in biomedical image analysis: before you go too deep

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

Generative Data-Driven Dynamic Deep Learning Classifier Selection for Hyperspectral Image Classification

Abstract: Deep learning has emerged as a critical paradigm in hyperspectral image (HSI) classification, addressing the inherent challenges posed by high-dimensional data and limited labeled samples.
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

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 ...
GitHub

deep-learning-project

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 ...
Frontiers

Deep learning-based classification of multiple fundus diseases using ultra-widefield images

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 ...