{"id":"https://openalex.org/W4410029391","doi":"https://doi.org/10.1109/lgrs.2025.3566444","title":"A CNNs-Transformer Hybrid Masked Autoencoder With Contrastive Learning for Landslide Extraction","display_name":"A CNNs-Transformer Hybrid Masked Autoencoder With Contrastive Learning for Landslide Extraction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410029391","doi":"https://doi.org/10.1109/lgrs.2025.3566444"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2025.3566444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3566444","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117411928","display_name":"Yasong Mi","orcid":null},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yasong Mi","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-8643-9767","affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Pengcheng Guo","orcid":"https://orcid.org/0009-0009-7545-6620"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengcheng Guo","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0009-7545-6620","affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ying Liang","orcid":"https://orcid.org/0009-0009-4322-1077"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Liang","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0009-4322-1077","affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026394989","display_name":"Junhuan Peng","orcid":"https://orcid.org/0000-0002-0587-9486"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhuan Peng","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0587-9486","affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422329","display_name":"Zhen Wang","orcid":"https://orcid.org/0000-0002-4318-9996"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Wang","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4318-9996","affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guodong Liu","orcid":"https://orcid.org/0009-0009-2146-8466"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guodong Liu","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0009-2146-8466","affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"School of Land Science and Technology, China Univers ity of Geosciences at Beijing, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115588592","display_name":"Wenwen Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenwen Wang","raw_affiliation_strings":["Key Laboratory of Survey, Monitoring and Protection of Natural Resources in Mining Cities, Ministry of Natural Resources, Jinzhong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Survey, Monitoring and Protection of Natural Resources in Mining Cities, Ministry of Natural Resources, Jinzhong, China","institution_ids":["https://openalex.org/I211433327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.0939,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.95315696,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9308000206947327,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9243000149726868,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.773919939994812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6119915246963501},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5080535411834717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49521127343177795},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47388309240341187},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3947005271911621},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.30890482664108276},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11326515674591064}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.773919939994812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6119915246963501},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5080535411834717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49521127343177795},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47388309240341187},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3947005271911621},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30890482664108276},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11326515674591064},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3566444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3566444","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.6399999856948853,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G4907757054","display_name":null,"funder_award_id":"L2424213","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2623518586","https://openalex.org/W2842511635","https://openalex.org/W2964309882","https://openalex.org/W2999729702","https://openalex.org/W3003882269","https://openalex.org/W4200108305","https://openalex.org/W4281710767","https://openalex.org/W4282559859","https://openalex.org/W4312785900","https://openalex.org/W4312981890","https://openalex.org/W4313128715","https://openalex.org/W4353066998","https://openalex.org/W4385348479","https://openalex.org/W4387092314","https://openalex.org/W4387331375","https://openalex.org/W4389776891","https://openalex.org/W4399849409","https://openalex.org/W4400046007","https://openalex.org/W4401834543","https://openalex.org/W4402215533","https://openalex.org/W6803870738","https://openalex.org/W6848688062"],"related_works":["https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W4405887298","https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2131735617","https://openalex.org/W2056912418","https://openalex.org/W2033213769","https://openalex.org/W4312376745"],"abstract_inverted_index":{"Landslide":[0],"extraction":[1,25,86,190],"plays":[2],"a":[3,40,72,84,150],"critical":[4],"role":[5],"in":[6],"disaster":[7],"prevention":[8],"and":[9,36,105,110,130,158],"mitigation.":[10],"However,":[11],"acquiring":[12],"sufficient":[13],"landslide":[14,85,92,189],"samples":[15],"is":[16,89,113,124,133],"often":[17,58],"challenging,":[18],"significantly":[19,187],"limiting":[20],"the":[21,99,103,117,120,136,140,160,170,183],"performance":[22],"of":[23,142,152],"existing":[24],"methods.":[26],"Self-supervised":[27],"learning":[28,80,132],"approaches,":[29],"such":[30],"as":[31,126,149],"masked":[32,75],"autoencoder":[33,76],"(MAE)":[34],"reconstruction":[35],"contrastive":[37,79,131],"learning,":[38],"offer":[39],"promising":[41],"solution":[42],"by":[43],"reducing":[44],"reliance":[45],"on":[46,135,176],"labeled":[47],"data.":[48],"Nonetheless,":[49],"Transformer-based":[50,122],"MAEs":[51,57],"are":[52],"computationally":[53],"intensive,":[54],"while":[55],"CNN-based":[56,161],"struggle":[59],"to":[60,101,163],"capture":[61,164],"global":[62,166],"contextual":[63],"information.":[64],"To":[65],"address":[66],"these":[67],"limitations,":[68],"this":[69],"letter":[70],"proposes":[71],"CNN-Transformer":[73],"hybrid":[74],"integrated":[77],"with":[78],"(CT-MAE)":[81],"for":[82,91,115,195],"pretraining":[83,116,185],"model.":[87],"HRNet":[88],"employed":[90],"extraction.":[93],"An":[94],"HRNet-based":[95],"MAE,":[96],"which":[97],"has":[98],"c-apability":[100],"preserve":[102],"resolution":[104],"effectively":[106],"integrate":[107],"both":[108,143],"shallow":[109],"deep":[111],"features,":[112],"proposed":[114,184],"HRNet.":[118],"Moreover,":[119],"traditional":[121],"MAE":[123,162],"applied":[125],"an":[127],"auxiliary":[128,146],"branch,":[129],"utilized":[134],"features":[137,167],"extracted":[138],"from":[139],"encoders":[141],"MAEs.":[144],"This":[145],"branch":[147],"serves":[148],"form":[151],"data":[153],"augmentation,":[154],"providing":[155],"supplementary":[156],"supervision,":[157],"enables":[159],"richer":[165],"without":[168],"modifying":[169],"underlying":[171],"CNN":[172],"architecture.":[173],"Experimental":[174],"results":[175],"two":[177],"publicly":[178],"available":[179],"datasets":[180],"demonstrate":[181],"that":[182],"approach":[186],"enhances":[188],"performance,":[191],"highlighting":[192],"its":[193],"potential":[194],"large-scale":[196],"applications.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}