Recent advances in deep learning have significantly transformed mineral classification methodologies, supplanting labour‐intensive manual approaches with automated, high-precision systems. By ...

Cataracts remain a leading cause of visual impairment worldwide, necessitating prompt and accurate diagnosis to avert irreversible blindness. In recent years, deep learning has emerged as a ...

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

The rapid development of deep learning in recent years is largely due to the rapid increase in the scale of data. The availability of large amounts of data is revolutionary for model training by the ...

Using whole-slide hematoxylin and eosin images from 214 patients with glioblastoma in The Cancer Genome Atlas (TCGA), a fine-tuned convolutional neural network model extracted deep learning features.

An international research team has developed a novel PV fault detection method based on deep learning of aerial images. The proposed methodology utilizes the convolutional neural network (CNN) ...

Researchers have leveraged deep learning techniques to enhance the image quality of a metalens camera. The new approach uses artificial intelligence to turn low-quality images into high-quality ones, ...

This study presents a deep learning model for breast cancer detection, achieving 99.24% accuracy and improving clinical ...