{"id":"https://openalex.org/W4404577296","doi":"https://doi.org/10.1109/icmlca63499.2024.10754176","title":"Change Detection of Open Pit Mining Areas in Remote Sensing Images Based on Coupled Local-Global Features","display_name":"Change Detection of Open Pit Mining Areas in Remote Sensing Images Based on Coupled Local-Global Features","publication_year":2024,"publication_date":"2024-10-18","ids":{"openalex":"https://openalex.org/W4404577296","doi":"https://doi.org/10.1109/icmlca63499.2024.10754176"},"language":"en","primary_location":{"id":"doi:10.1109/icmlca63499.2024.10754176","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icmlca63499.2024.10754176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Machine Learning and Computer Application (ICMLCA)","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/A5100367707","display_name":"Xiaolei Wang","orcid":"https://orcid.org/0000-0001-9431-0058"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolei Wang","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture,Beijing,China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101849062","display_name":"Jingguo Lv","orcid":"https://orcid.org/0000-0002-4424-5478"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingguo Lv","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture,Beijing,China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457270","display_name":"Xiaojuan Zhang","orcid":"https://orcid.org/0009-0005-1579-6851"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojuan Zhang","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture,Beijing,China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056891097","display_name":"Aiyuan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aiyuan Zhang","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture,Beijing,China","institution_ids":["https://openalex.org/I62853816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I62853816"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22317658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"224","last_page":"227"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9907000064849854,"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"}},"topics":[{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9907000064849854,"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"}},{"id":"https://openalex.org/T13065","display_name":"Mining Techniques and Economics","score":0.9787999987602234,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.9693999886512756,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5742985010147095},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5569283962249756},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5467638969421387},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2682538330554962},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21341031789779663}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5742985010147095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5569283962249756},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5467638969421387},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2682538330554962},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21341031789779663}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlca63499.2024.10754176","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icmlca63499.2024.10754176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Machine Learning and Computer Application (ICMLCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3],"coupled":[4],"local-global":[5,37],"feature-based":[6],"change":[7,160],"detection":[8,93,116],"method":[9,141],"Swin-LGCNet":[10,100],"is":[11,52,76,118],"proposed":[12],"for":[13,158],"remote":[14,150],"sensing":[15,151],"image":[16],"open":[17,166],"pit":[18,167],"mining":[19,168],"areas":[20],"The":[21,48,95,140],"model":[22],"interactively":[23],"fuses":[24],"local":[25,111],"and":[26,32,62,88,110,114,131,137,153,162],"global":[27,107],"features":[28,87],"extracted":[29],"by":[30],"ResNet":[31],"Swin":[33],"Transformer":[34],"through":[35],"the":[36,44,59,64,73,81,84,91,102,115,123,146],"feature":[38,45],"coupling":[39],"module,":[40],"which":[41,57],"effectively":[42],"improves":[43],"expression":[46],"capability.":[47],"Mish":[49],"activation":[50],"function":[51],"used":[53],"instead":[54],"of":[55,145,149],"ReLU,":[56],"reduces":[58],"information":[60,108],"loss":[61],"enhances":[63],"model's":[65],"ability":[66],"to":[67,78],"capture":[68],"complex":[69],"changing":[70],"features.":[71],"Meanwhile,":[72],"differential":[74],"operation":[75],"introduced":[77],"further":[79],"enhance":[80],"difference":[82],"between":[83],"dual-time":[85],"phase":[86],"significantly":[89,119],"reduce":[90],"leakage":[92],"rate.":[94],"experimental":[96],"results":[97],"show":[98],"that":[99],"outperforms":[101],"traditional":[103],"network":[104],"in":[105,134,165],"both":[106],"extraction":[109],"detail":[112],"performance,":[113],"accuracy":[117],"improved":[120],"compared":[121],"with":[122],"comparison":[124],"networks,":[125],"such":[126],"as":[127],"PSPNet,":[128],"Deeplabv3+,":[129],"UNet":[130],"UNet++,":[132],"especially":[133],"boundary":[135],"identification":[136],"noise":[138],"suppression.":[139],"makes":[142],"full":[143],"use":[144],"temporal":[147],"sequence":[148],"images,":[152],"provides":[154],"efficient":[155],"technical":[156],"support":[157],"dynamic":[159],"monitoring":[161],"ecological":[163],"protection":[164],"areas.":[169]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
