IEEE

Single Remote Sensing Image Super-Resolution via Convolutional Neural Network and Diffusion Model

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 ...
IEEE

High-Resolution Image Reconstruction Using Convolutional Neural Network-Based Deep Learning Models

Abstract: This paper presents an optimized lightweight Super-Resolution Convolutional Neural Network (SRCNN) capable of reconstructing high-quality images with strong fidelity. The proposed framework ...
Frontiers

A vision-based drowsiness detection system for railway operators using lightweight convolutional neural networks

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 New York Times

How Trump Is Using Fake Imagery to Attack Enemies and Rouse Supporters

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 ...
PNAS

Descattering and image restoration with a transformer-based neural network in deep tissue imaging

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 ...
PNAS

Four-hour thunderstorm nowcasting using a deep diffusion model for satellite data

Severe storms threaten human lives and cause substantial economic losses. In this work, we present a storm nowcasting system based on satellite data and AI techniques. It extends forecasts up to 4 h ...