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(NSFC)","award":["2021YFC3000401"],"award-info":[{"award-number":["2021YFC3000401"]}]},{"name":"National Natural Science Foundation of China (NSFC)","award":["2022-YF05-01090-SN"],"award-info":[{"award-number":["2022-YF05-01090-SN"]}]},{"name":"National Natural Science Foundation of China (NSFC)","award":["SKLGP2018Z010"],"award-info":[{"award-number":["SKLGP2018Z010"]}]},{"name":"National Natural Science Foundation of China (NSFC)","award":["41871303"],"award-info":[{"award-number":["41871303"]}]},{"name":"National Natural Science Foundation of China (NSFC)","award":["kj-2021-3"],"award-info":[{"award-number":["kj-2021-3"]}]},{"name":"Department of Natural Resources of Sichuan Province","award":["2021YFC3000401"],"award-info":[{"award-number":["2021YFC3000401"]}]},{"name":"Department of Natural Resources of Sichuan Province","award":["2022-YF05-01090-SN"],"award-info":[{"award-number":["2022-YF05-01090-SN"]}]},{"name":"Department of Natural Resources of Sichuan Province","award":["SKLGP2018Z010"],"award-info":[{"award-number":["SKLGP2018Z010"]}]},{"name":"Department of Natural Resources of Sichuan Province","award":["41871303"],"award-info":[{"award-number":["41871303"]}]},{"name":"Department of Natural Resources of Sichuan Province","award":["kj-2021-3"],"award-info":[{"award-number":["kj-2021-3"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>For emergency rescue and damage assessment after an earthquake, quick detection of seismic landslides in the affected areas is crucial. The purpose of this study is to quickly determine the extent and size of post-earthquake seismic landslides using a small amount of post-earthquake seismic landslide imagery data. This information will serve as a foundation for emergency rescue efforts, disaster estimation, and other actions. In this study, Wenchuan County, Sichuan Province, China\u2019s 2008 post-quake Unmanned Air Vehicle (UAV) remote sensing images are used as the data source. ResNet-50, ResNet-101, and Swin Transformer are used as the backbone networks of Mask R-CNN to train and identify seismic landslides in post-quake UAV images. The training samples are then augmented by data augmentation methods, and transfer learning methods are used to reduce the training time required and enhance the generalization of the model. Finally, transfer learning was used to apply the model to seismic landslide imagery from Haiti after the earthquake that was not calibrated. With Precision and F1 scores of 0.9328 and 0.9025, respectively, the results demonstrate that Swin Transformer performs better as a backbone network than the original Mask R-CNN, YOLOv5, and Faster R-CNN. In Haiti\u2019s post-earthquake images, the improved model performs significantly better than the original model in terms of accuracy and recognition. The model for identifying post-earthquake seismic landslides developed in this paper has good generalizability and transferability as well as good application potential in emergency responses to earthquake disasters, which can offer strong support for post-earthquake emergency rescue and disaster assessment.<\/jats:p>","DOI":"10.3390\/rs14163928","type":"journal-article","created":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T23:44:03Z","timestamp":1660607043000},"page":"3928","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":73,"title":["Fast Seismic Landslide Detection Based on Improved Mask R-CNN"],"prefix":"10.3390","volume":"14","author":[{"given":"Rao","family":"Fu","sequence":"first","affiliation":[{"name":"School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"He","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8856-8746","authenticated-orcid":false,"given":"Gang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China"},{"name":"State Key Laboratory of Geological Hazard Prevention and Geological Environment Protection, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3741-8801","authenticated-orcid":false,"given":"Weile","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Geological Hazard Prevention and Geological Environment Protection, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaqi","family":"Mao","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minhui","family":"He","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyang","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1007\/s10064-009-0207-0","article-title":"Analysis of the Geo-Hazards Triggered by the 12 May 2008 Wenchuan Earthquake, China","volume":"68","author":"Huang","year":"2009","journal-title":"Bull. 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