ABSTRACT: The nearly analytic discretization of the frequency-domain wave equation produces large-scale, sparse, and ill-conditioned linear system, which challenge conventional iterative solvers. To ...

Abstract: We propose a novel spatiotemporal fusion method based on deep convolutional neural networks (CNNs) under the application background of massive remote sensing data. In the training stage, we ...

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 ...

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 ...

A research-ready implementation of video super-resolution using deep learning models. This project provides state-of-the-art models including SRCNN, VDSR, EDVR, and BasicVSR++ for enhancing video ...

This project implements DCGAN (Deep Convolutional GAN) for generating realistic images. The architecture uses convolutional layers in both generator and discriminator networks. It includes batch ...