A Robust CNN Framework for Change Detection Analysis From Bitemporal Remote Sensing Images-Reference-Cited by-同舟云学术

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A Robust CNN Framework for Change Detection Analysis From Bitemporal Remote Sensing Images

Published:2024 Issue: Volume:17 Page:12637-12648
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

N Sravya¹^ORCID,Bhaduka Khyati¹,Lal Shyam¹^ORCID,Nalini J²^ORCID,Sudhakar Reddy Chintala³^ORCID

Affiliation:

1. Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Mangalore, India

2. Aerial Services and Digital Mapping Division, National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad, India

3. Forest Biodiversity and Ecology Division, National Remote Sensing Centre, Indian Space Research Organization (ISRO), Hyderabad, India

Funder

RESPOND Scheme of Indian Space Research Organization

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/4609443/10330207/10584262.pdf?arnumber=10584262

Reference43 articles.

1. Review Article Digital change detection techniques using remotely-sensed data

2. Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat Imagery Change Detection Methods

3. Urban Change Detection Based on Dempster–Shafer Theory for Multitemporal Very High-Resolution Imagery

4. Image change detection algorithms: a systematic survey

5. Quantifying Disaster Physical Damage Using Remote Sensing Data—A Technical Work Flow and Case Study of the 2014 Ludian Earthquake in China

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