{"id":"https://openalex.org/W4402263262","doi":"https://doi.org/10.1109/igarss53475.2024.10642657","title":"Enhancing Change Detection Robustness: A Whitening Transformation Approach","display_name":"Enhancing Change Detection Robustness: A Whitening Transformation Approach","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402263262","doi":"https://doi.org/10.1109/igarss53475.2024.10642657"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10642657","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10642657","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":"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/A5053066562","display_name":"Fei Liang","orcid":"https://orcid.org/0000-0002-4184-7844"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fei Liang","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Shaanxi,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005627827","display_name":"Qi Zang","orcid":"https://orcid.org/0009-0009-0846-7987"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zang","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Shaanxi,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108166730","display_name":"Zhengyao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhengyao Wang","raw_affiliation_strings":["Aerial Photography and Remote Sensing Group Co. Ltd.,Xi&#x2019;an,China,710199"],"affiliations":[{"raw_affiliation_string":"Aerial Photography and Remote Sensing Group Co. Ltd.,Xi&#x2019;an,China,710199","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077347597","display_name":"Yang Hu","orcid":"https://orcid.org/0000-0002-7724-3786"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Hu","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Shaanxi,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085893076","display_name":"Dou Quan","orcid":"https://orcid.org/0000-0001-6943-4657"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dou Quan","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Shaanxi,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115595775","display_name":"Shuang Wang","orcid":"https://orcid.org/0000-0002-0378-9583"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Wang","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Shaanxi,China"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Shaanxi,China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5053066562"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12555854,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10342","last_page":"10345"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.6065000295639038,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.6065000295639038,"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/T11864","display_name":"Supply Chain Resilience and Risk Management","score":0.599399983882904,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7720929384231567},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.595231294631958},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4419615864753723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35342320799827576}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7720929384231567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.595231294631958},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4419615864753723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35342320799827576},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10642657","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10642657","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":[{"score":0.5,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2154451793","https://openalex.org/W2800255560","https://openalex.org/W2805152403","https://openalex.org/W3169545167","https://openalex.org/W3176330035","https://openalex.org/W4384159545","https://openalex.org/W4386076503"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"The":[0],"vast":[1],"amount":[2],"of":[3,82],"remote":[4,38],"sensing":[5,39],"data":[6],"has":[7],"been":[8],"instrumental":[9],"in":[10,28,33,49],"supporting":[11],"research":[12],"on":[13,18,63],"change":[14,59],"detection":[15,60],"algorithms":[16],"based":[17,62],"deep":[19],"learning.However,":[20],"factors":[21],"such":[22],"as":[23],"geographical":[24],"changes":[25],"and":[26,99],"variations":[27],"sensor":[29],"parameters":[30],"can":[31],"result":[32],"significant":[34],"style":[35,79],"differences":[36,71],"between":[37],"images":[40],"at":[41],"different":[42],"time":[43],"points,":[44],"leading":[45],"to":[46,68,95,104],"a":[47,58],"decline":[48],"model":[50],"performance.To":[51],"address":[52],"this":[53,55],"issue,":[54],"paper":[56],"proposes":[57],"algorithm":[61],"whitening":[64],"feature":[65],"extraction,":[66],"aiming":[67],"alleviate":[69],"distribution":[70],"by":[72],"decoupling":[73],"domain-invariant":[74],"discriminative":[75],"features":[76],"from":[77,91,100],"domain-specific":[78],"features.The":[80],"effectiveness":[81],"the":[83,92,96,101,105],"proposed":[84],"method":[85],"is":[86],"demonstrated":[87],"through":[88],"transfer":[89],"experiments":[90],"SVCD":[93],"dataset":[94,98,103],"SZADA":[97,106],"SYSU":[102],"dataset.":[107]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
