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 ...
Live Science

'Thermodynamic computer' can mimic AI neural networks — using orders of magnitude less energy to generate images

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require. When you purchase through links on our site, we may earn an affiliate ...
IEEE

A Cosine Network for Image Super-Resolution

Abstract: Deep convolutional neural networks can use hierarchical information to progressively extract structural information to recover high-quality images. However, preserving the effectiveness of ...
Scientific Research Publishing

Seismic Multiple Attenuation Method Based on Spectral Subtraction and Convolutional Dual Attention Mechanism ()

1 College of Science, Tianjin University of Technology and Education, Tianjin, China. 2 Lvliang Vocational and Technical College, Lvliang, China. Multiple reflections in seismic exploration data ...
Scientific Research Publishing

Dual-Dilated Large Kernel Convolution for Visual Attention Network ()

Visual Attention Networks (VANs) leveraging Large Kernel Attention (LKA) have demonstrated remarkable performance in diverse computer vision tasks, often outperforming Vision Transformers (ViTs) in ...