{"id":"https://openalex.org/W4402264587","doi":"https://doi.org/10.1109/igarss53475.2024.10640432","title":"Swinlitekd: Optimizing Landslide Recognition Using Swin-Transformer Networks with Knowledge Distillation","display_name":"Swinlitekd: Optimizing Landslide Recognition Using Swin-Transformer Networks with Knowledge Distillation","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402264587","doi":"https://doi.org/10.1109/igarss53475.2024.10640432"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10640432","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10640432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5107013916","display_name":"Huang Renxiang","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huang Renxiang","raw_affiliation_strings":["China University of Geosciences,School of Geophysics and Geomatics,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Geosciences,School of Geophysics and Geomatics,Wuhan,China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chen Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Tao","raw_affiliation_strings":["China University of Geosciences,School of Geophysics and Geomatics,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Geosciences,School of Geophysics and Geomatics,Wuhan,China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32349692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8316","last_page":"8319"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9998000264167786,"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":0.9998000264167786,"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/T10930","display_name":"Flood Risk Assessment and Management","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9732000231742859,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.667101263999939},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6597659587860107},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.4737618565559387},{"id":"https://openalex.org/keywords/landslide","display_name":"Landslide","score":0.47168877720832825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3711206316947937},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.23871132731437683},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20328989624977112},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.15871912240982056},{"id":"https://openalex.org/keywords/geotechnical-engineering","display_name":"Geotechnical engineering","score":0.14679569005966187},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.10538271069526672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.667101263999939},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6597659587860107},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.4737618565559387},{"id":"https://openalex.org/C186295008","wikidata":"https://www.wikidata.org/wiki/Q167903","display_name":"Landslide","level":2,"score":0.47168877720832825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3711206316947937},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.23871132731437683},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20328989624977112},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.15871912240982056},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.14679569005966187},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.10538271069526672},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10640432","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10640432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.5899999737739563,"display_name":"Climate action"}],"awards":[],"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":8,"referenced_works":["https://openalex.org/W191575298","https://openalex.org/W1983769347","https://openalex.org/W1995085431","https://openalex.org/W2168899452","https://openalex.org/W2578756457","https://openalex.org/W2912361013","https://openalex.org/W2947982909","https://openalex.org/W2981581709"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2389676928","https://openalex.org/W3169474304","https://openalex.org/W2369104181","https://openalex.org/W3201652628","https://openalex.org/W4212972401","https://openalex.org/W2389287188","https://openalex.org/W3081499580","https://openalex.org/W2615020820"],"abstract_inverted_index":{"Recognizing":[0],"landslides":[1],"effectively":[2],"is":[3,103],"crucial":[4,89],"for":[5],"disaster":[6],"prevention":[7],"and":[8,28,62,77,108,115],"post-disaster":[9],"rescue":[10],"operations.":[11],"Our":[12],"SwinLiteKD,":[13],"an":[14],"innovative":[15],"knowledge":[16],"distillation":[17],"network":[18],"based":[19],"on":[20],"Swin-Transformer,":[21,61],"addresses":[22],"challenges":[23],"related":[24],"to":[25,53,59],"model":[26,56,87],"runtimes":[27],"inefficiencies":[29],"in":[30,36,40,92,122],"current":[31],"deep":[32],"learning":[33],"approaches.":[34],"Validated":[35],"a":[37],"landslide-prone":[38],"region":[39],"Zigui":[41],"County,":[42],"Hubei":[43],"Province,":[44],"China,":[45],"our":[46,86],"proposed":[47],"method":[48],"incorporates":[49],"landslide":[50,93,126],"influencing":[51],"factors":[52],"significantly":[54],"enhance":[55],"performance.":[57],"Compared":[58],"ResNet50,":[60],"DeiT,":[63,116],"SwinLiteKD":[64,118],"achieves":[65],"superior":[66],"Overall":[67],"Accuracy":[68],"(OA:":[69],"97.0000%),":[70],"Precision":[71],"(97.1698%),":[72],"Recall":[73],"(96.9999%),":[74],"F1":[75],"(97.0848%),":[76],"Kappa":[78],"(93.99%).":[79],"With":[80],"the":[81],"lowest":[82],"number":[83],"of":[84],"FLOPs,":[85],"ensures":[88],"computational":[90],"efficiency":[91],"recognition":[94,127],"after":[95],"geological":[96],"disasters,":[97],"requiring":[98],"only":[99],"4.4987":[100],"GFLOPs.":[101],"This":[102],"0.1553":[104],"GFLOPs,":[105,107],"0.0723":[106],"0.3597":[109],"GFLOPs":[110],"less":[111],"than":[112],"ResNet,":[113],"Swin,":[114],"respectively.":[117],"demonstrates":[119],"excellent":[120],"adaptability":[121],"scenarios":[123],"demanding":[124],"swift":[125],"post-geological":[128],"disasters.":[129]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
