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Journal · 2022

IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images

Md. Abdul Alim Sheikh, Tanmoy Maity, Alok Kole

Cited by 16 IEEE Access DOI

Abstract

No abstract has been published for this record yet. The publisher has not deposited one — you can read the paper via its DOI.

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Publication details

Venue: IEEE Access
Type: Journal · 2022
DOI: 10.1109/ACCESS.2022.3164401
Citations: 16 · via Crossref, 18 September 2026

Cite this publication

Copy a ready-formatted citation in your preferred style.

APA

Sheikh, M. A. A., Maity, T., & Kole, A. (2022). IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3164401

Harvard

Sheikh, M.A.A., Maity, T. and Kole, A. (2022) 'IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images', IEEE Access. doi: 10.1109/ACCESS.2022.3164401.

IEEE

M. A. A. Sheikh, T. Maity, and A. Kole, "IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images," IEEE Access, 2022. doi: 10.1109/ACCESS.2022.3164401.

Vancouver

Sheikh MAA, Maity T, Kole A. IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images. IEEE Access. 2022. doi: 10.1109/ACCESS.2022.3164401.

MLA

Sheikh, Md. Abdul Alim, et al.. "IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images." IEEE Access, 2022. https://doi.org/10.1109/ACCESS.2022.3164401.

Chicago

Sheikh, M. A. A., Maity, T., Kole, A.. "IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images." IEEE Access (2022). https://doi.org/10.1109/ACCESS.2022.3164401.

BibTeX

@article{sheikh2022, title={IRU-Net: An Efficient End-to-End Network for Automatic Building Extraction From Remote Sensing Images}, author={Sheikh, Md. Abdul Alim and Maity, Tanmoy and Kole, Alok}, journal={IEEE Access}, year={2022}, doi={10.1109/ACCESS.2022.3164401}, }

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