Reconstructing higher-resolution four-dimensional time-varying volumetric data

IF 3.2 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Connection Science Pub Date : 2023-12-08 DOI:10.1080/09540091.2023.2289837

Ji Ma, Jinjin Chen

引用次数: 0

Abstract

We have witnessed substantial growth in super-resolution research within the computer vision community. Unlike previous works that mainly focus on the super-resolution synthesis of images, videos, ...

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重建更高分辨率的四维时变容积数据

我们见证了计算机视觉领域超分辨率研究的大幅增长。不同于以往主要关注图像、视频和图像处理的超分辨率合成的研究，超分辨率研究在计算机视觉领域有了长足的发展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Connection Science 工程技术-计算机：理论方法

CiteScore

6.50

自引率

39.60%

发文量

审稿时长

3 months

期刊介绍： Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing. A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.