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) ...

Deep Learning is probably the most popular form of machine learning at this time. Although not every problem boils down to a deep learning model, in domains such as computer vision and natural ...

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, ...