RSCDNet: A Robust Deep Learning Architecture for Change Detection From Bi-Temporal High Resolution Remote Sensing Images-Reference-Cited by-同舟云学术

RSCDNet: A Robust Deep Learning Architecture for Change Detection From Bi-Temporal High Resolution Remote Sensing Images

Published:2023-04 Issue:2 Volume:7 Page:537-551
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Deepanshi ¹,Barkur Rahasya¹^ORCID,Suresh Devishi¹^ORCID,Lal Shyam¹^ORCID,Reddy C. Sudhakar²^ORCID,Diwakar P. G.³

Affiliation:

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

2. National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad, India

3. Indian Space Research Organization (ISRO), Bangalore, India

Funder

Indian Space Research Organization

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computational Mathematics,Control and Optimization,Computer Science Applications

Link

Reference42 articles.

3. U-Net: Convolutional networks for biomedical image segmentation;ronneberger;Proc Int Conf Med Image Comput Comput -Assist Interv,0

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