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 ...
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 ...
1 Guangzhou Railway Polytechnic, Guangzhou, China. 2 School of Intelligent Construction and Civil Engineering, Zhongyuan University of Technology, Zhengzhou, China. 3 Research Center for Wind ...
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 ...
Poor product images kill sales faster than high shipping costs. In 2025, 93% of consumers consider visual appearance the key deciding factor in purchasing decisions. Low-resolution product photos ...
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 ...
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