From facial recognition on smartphones to humanoid robots, computer vision technology, which serves as the eyes of artificial ...

Deep learning high-content imaging is rapidly reshaping image-based screening in the modern laboratory environment. As high-content screening (HCS) generates increasingly large and complex datasets, ...

A new explainable deep learning framework could help greenhouse operators forecast crop yields and energy use more accurately while showing which environmental factors drive those predictions, ...

Abstract: Recent diffusion generative model super-resolution (SR) methods have made great progress in remote sensing image quality enhancement. However, the representation learning capability of ...

High-resolution magnetic resonance vessel wall imaging (HR-VWI) is an advanced MR imaging technique that can directly visualize intracranial vessel walls and detect subtle pathological changes. HR-VWI ...

Propose a novel and effective image super-resolution method that overcomes the shortcomings of existing methods and improves image super-resolution quality. Multi-level feature fusion adopts the ...

In recent years, single image super-resolution (SISR) based on deep learning has achieved excellent results. However, the consequent elevated computational and storage expenses limit its ...

This research addresses the challenge of monitoring railway driver drowsiness using a real-time, vision-based system powered by convolutional neural networks, specifically the YOLOv8 architecture ...

The era of A.I. propaganda is here — and President Trump is an enthusiastic participant. After nationwide protests this weekend against Mr. Trump’s administration, the president posted an ...

The significant contributions of this work are threefold. First, it leverages deep learning to extend in vivo imaging depth of two-photon excitation fluorescence microscopy, far beyond the depths ...