Optimizing Spatial Sensing Performance with Kriging and SRGAN – A Feasibility Study-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Optimizing Spatial Sensing Performance with Kriging and SRGAN – A Feasibility Study

Published:2023-10-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE SENSORS
language:
Short-container-title:

Author:

Tan Roe Djer¹,Patade Omkar¹,Wang Huaxia²,Yang Chulho²,Lee Dongchan³

Affiliation:

1. Watson Graduate School of Management, Oklahoma State University,Stillwater,OK,USA

2. Oklahoma State University,Division of Engineering Technology,Stillwater,OK,USA

3. AI&Mechanical System Center, Institute for Advanced Engineering (IAE),Yongin-si,South Korea

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10324456/10324848/10325319.pdf?arnumber=10325319

Reference16 articles.

1. Image Quality Assessment through FSIM, SSIM, MSE and PSNR—A Comparative Study

2. Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution

3. Refining Architectures of Deep Convolutional Neural Networks

4. Evaluation of SRGAN Algorithm for Superresolution of Satellite Imagery on Different Sensors

5. Very Deep Convolutional Networks for Large-Scale Image Recognition;simonyan;ArXiv org,2014

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP