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Peer-reviewed Journals (306)

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1	Material Type: Article	A review of building detection from very high resolution optical remote sensing images GIScience and remote sensing, 2022-12, Vol.59 (1), p.1199-1225 [Peer Reviewed Journal] 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2022 ;ISSN: 1548-1603 ;EISSN: 1943-7226 ;DOI: 10.1080/15481603.2022.2101727 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
2	Material Type: Article	Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters Remote sensing (Basel, Switzerland), 2018-01, Vol.10 (1), p.144 [Peer Reviewed Journal] ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs10010144 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
3	Material Type: Article	SNNFD, spiking neural segmentation network in frequency domain using high spatial resolution images for building extraction International journal of applied earth observation and geoinformation, 2022-08, Vol.112, p.102930, Article 102930 [Peer Reviewed Journal] 2022 ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2022.102930 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
4	Material Type: Article	DPENet: Dual-path extraction network based on CNN and transformer for accurate building and road extraction International journal of applied earth observation and geoinformation, 2023-11, Vol.124, p.103510, Article 103510 [Peer Reviewed Journal] 2023 ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2023.103510 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
5	Material Type: Article	A co-learning method to utilize optical images and photogrammetric point clouds for building extraction International journal of applied earth observation and geoinformation, 2023-02, Vol.116, p.103165, Article 103165 [Peer Reviewed Journal] 2023 The Authors ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2022.103165 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
6	Material Type: Article	Deep Learning-Based Building Extraction from Remote Sensing Images: A Comprehensive Review Energies (Basel), 2021-12, Vol.14 (23), p.7982 [Peer Reviewed Journal] 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en14237982 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
7	Material Type: Article	Building and road detection from remote sensing images based on weights adaptive multi-teacher collaborative distillation using a fused knowledge International journal of applied earth observation and geoinformation, 2023-11, Vol.124, p.103522, Article 103522 [Peer Reviewed Journal] 2023 ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2023.103522 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
8	Material Type: Article	BRRNet: A Fully Convolutional Neural Network for Automatic Building Extraction From High-Resolution Remote Sensing Images Remote sensing (Basel, Switzerland), 2020-03, Vol.12 (6), p.1050 [Peer Reviewed Journal] 2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12061050 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
9	Material Type: Article	CaSaFormer: A cross- and self-attention based lightweight network for large-scale building semantic segmentation International journal of applied earth observation and geoinformation, 2024-06, Vol.130, p.103942, Article 103942 [Peer Reviewed Journal] 2024 ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2024.103942 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
10	Material Type: Article	Exploring the user guidance for more accurate building segmentation from high-resolution remote sensing images International journal of applied earth observation and geoinformation, 2024-02, Vol.126, p.103609, Article 103609 [Peer Reviewed Journal] 2024 The Authors ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2023.103609 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
11	Material Type: Article	Automatic identification of utilizable rooftop areas in digital surface models for photovoltaics potential assessment Applied energy, 2022-01, Vol.306 [Peer Reviewed Journal] ISSN: 1872-9118 ;ISSN: 0306-2619 ;DOI: 10.1016/j.apenergy.2021.118033 Digital Resources/Online E-Resources View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
12	Material Type: Article	Semantic Segmentation of Urban Buildings from VHR Remote Sensing Imagery Using a Deep Convolutional Neural Network Remote sensing (Basel, Switzerland), 2019-08, Vol.11 (15), p.1774 [Peer Reviewed Journal] 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs11151774 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
13	Material Type: Article	Building Extraction from Remote Sensing Images with Sparse Token Transformers Remote sensing (Basel, Switzerland), 2021-11, Vol.13 (21), p.4441 [Peer Reviewed Journal] 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs13214441 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
14	Material Type: Article	GCCINet: Global feature capture and cross-layer information interaction network for building extraction from remote sensing imagery International journal of applied earth observation and geoinformation, 2022-11, Vol.114, p.103046, Article 103046 [Peer Reviewed Journal] 2022 The Author(s) ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2022.103046 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
15	Material Type: Article	A Deep Learning Approach on Building Detection from Unmanned Aerial Vehicle-Based Images in Riverbank Monitoring Sensors (Basel, Switzerland), 2018-11, Vol.18 (11), p.3921 [Peer Reviewed Journal] 2018 by the authors. 2018 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s18113921 ;PMID: 30441771 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
16	Material Type: Article	Building Extraction Based on U-Net with an Attention Block and Multiple Losses Remote sensing (Basel, Switzerland), 2020-05, Vol.12 (9), p.1400 [Peer Reviewed Journal] 2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12091400 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
17	Material Type: Article	Automatic Building Extraction from Google Earth Images under Complex Backgrounds Based on Deep Instance Segmentation Network Sensors (Basel, Switzerland), 2019-01, Vol.19 (2), p.333 [Peer Reviewed Journal] 2019 by the authors. 2019 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s19020333 ;PMID: 30650645 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
18	Material Type: Article	Extracting buildings from high-resolution remote sensing images by deep ConvNets equipped with structural-cue-guided feature alignment International journal of applied earth observation and geoinformation, 2022-09, Vol.113, p.102970, Article 102970 [Peer Reviewed Journal] 2022 The Author(s) ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2022.102970 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
19	Material Type: Article	Robust Building Extraction for High Spatial Resolution Remote Sensing Images with Self-Attention Network Sensors (Basel, Switzerland), 2020-12, Vol.20 (24), p.7241 [Peer Reviewed Journal] 2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 by the authors. 2020 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s20247241 ;PMID: 33348752 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by
20	Material Type: Article	Building extraction from remote sensing images using deep residual U-Net European journal of remote sensing, 2022-12, Vol.55 (1), p.71-85 [Peer Reviewed Journal] 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2022 ;2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2279-7254 ;EISSN: 2279-7254 ;DOI: 10.1080/22797254.2021.2018944 Full text available View Online Details Recommendations Reviews Times Cited External Links Citations Cited by

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Results 1 - 20 of 340 for All Library Resources

2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2022 ;ISSN: 1548-1603 ;EISSN: 1943-7226 ;DOI: 10.1080/15481603.2022.2101727

ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs10010144

2022 ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2022.102930

2023 ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2023.103510

2023 The Authors ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2022.103165

2023 ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2023.103522

2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12061050

2024 ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2024.103942

2024 The Authors ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2023.103609

ISSN: 1872-9118 ;ISSN: 0306-2619 ;DOI: 10.1016/j.apenergy.2021.118033

2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs11151774

2022 The Author(s) ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2022.103046

2018 by the authors. 2018 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s18113921 ;PMID: 30441771

2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12091400

2019 by the authors. 2019 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s19020333 ;PMID: 30650645

2022 The Author(s) ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2022.102970

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