Change Detection using Deep Learning and Machine Learning Techniques for Multispectral Satellite Images

Author:

Abstract

Change detection is used to find whether the changes happened or not between two different time periods using remote sensing images. We can use various machine learning techniques and deep learning techniques for the change detection analysis using remote sensing images. This paper mainly focused on computational and performance analysis of both techniques in the application of change detection .For each approach, we considered ten different kinds of algorithms and evaluated the performance. Moreover, in this research work, we have analyzed merits and demerits of each method which have used to change detection.

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Electrical and Electronic Engineering,Mechanics of Materials,Civil and Structural Engineering,General Computer Science

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Change Detection Mechanism Over Multi-spectral Images Using Machine-Learning Techniques;Lecture Notes in Electrical Engineering;2024

2. Semi-Supervised Detection of Detailed Ground Feature Changes and Its Impact on Land Surface Temperature;Atmosphere;2023-12-12

3. Machine Learning and Deep Learning powered satellite communications: Enabling technologies, applications, open challenges, and future research directions;International Journal of Satellite Communications and Networking;2023-05-14

4. Investigation of Deep Learning Methodologies in Satellite Image based Ship Detection;2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS);2022-04-07

5. A Hybrid CNN-RNN Deep Learning Network for Deriving Cyclonic Change Map from Bi-Temporal SAR Images;Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications;2022

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

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3