{"id":"https://openalex.org/W4297540225","doi":"https://doi.org/10.3390/ijgi11100503","title":"ICD: VHR-Oriented Interactive Change-Detection Algorithm","display_name":"ICD: VHR-Oriented Interactive Change-Detection Algorithm","publication_year":2022,"publication_date":"2022-09-27","ids":{"openalex":"https://openalex.org/W4297540225","doi":"https://doi.org/10.3390/ijgi11100503"},"language":"en","primary_location":{"id":"doi:10.3390/ijgi11100503","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi11100503","pdf_url":"https://www.mdpi.com/2220-9964/11/10/503/pdf?version=1664444024","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2220-9964/11/10/503/pdf?version=1664444024","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026054433","display_name":"Zhuoran Jiang","orcid":"https://orcid.org/0000-0003-4734-5535"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuoran Jiang","raw_affiliation_strings":["School of Geographic Sciences, Nanjing Normal University, Nanjing 210023, China"],"raw_orcid":"https://orcid.org/0000-0003-4734-5535","affiliations":[{"raw_affiliation_string":"School of Geographic Sciences, Nanjing Normal University, Nanjing 210023, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101601589","display_name":"Xinxin Zhou","orcid":"https://orcid.org/0000-0003-3783-3965"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinxin Zhou","raw_affiliation_strings":["School of Geography and Bioinformatics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geography and Bioinformatics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030936507","display_name":"Wei Cao","orcid":"https://orcid.org/0000-0002-0904-1146"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Cao","raw_affiliation_strings":["Nanjing Guotu Information Industry Co., Ltd., Nanjing 210000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Guotu Information Industry Co., Ltd., Nanjing 210000, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049804667","display_name":"Sun Zaihong","orcid":null},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zaihong Sun","raw_affiliation_strings":["School of Geographic Sciences, Nanjing Normal University, Nanjing 210023, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geographic Sciences, Nanjing Normal University, Nanjing 210023, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059684766","display_name":"Changbin Wu","orcid":"https://orcid.org/0000-0003-3358-7138"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Changbin Wu","raw_affiliation_strings":["School of Geographic Sciences, Nanjing Normal University, Nanjing 210023, China"],"raw_orcid":"https://orcid.org/0000-0003-3358-7138","affiliations":[{"raw_affiliation_string":"School of Geographic Sciences, Nanjing Normal University, Nanjing 210023, China","institution_ids":["https://openalex.org/I152031979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5059684766"],"corresponding_institution_ids":["https://openalex.org/I152031979"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.226,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56735137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"11","issue":"10","first_page":"503","last_page":"503"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9570000171661377,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9261000156402588,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.8072381019592285},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6136243939399719},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5639150738716125},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5618752837181091},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5483459234237671},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5467230081558228},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5313014984130859},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4977877140045166},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.43049803376197815},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40686842799186707},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3629581928253174},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3627172112464905},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35753333568573},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07798683643341064}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8072381019592285},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6136243939399719},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5639150738716125},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5618752837181091},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5483459234237671},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5467230081558228},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5313014984130859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4977877140045166},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.43049803376197815},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40686842799186707},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3629581928253174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3627172112464905},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35753333568573},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07798683643341064},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/ijgi11100503","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi11100503","pdf_url":"https://www.mdpi.com/2220-9964/11/10/503/pdf?version=1664444024","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1d914376a5304a88b88a5b38d83a83d3","is_oa":true,"landing_page_url":"https://doaj.org/article/1d914376a5304a88b88a5b38d83a83d3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information, Vol 11, Iss 10, p 503 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2220-9964/11/10/503/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/ijgi11100503","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information; Volume 11; Issue 10; Pages: 503","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/ijgi11100503","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi11100503","pdf_url":"https://www.mdpi.com/2220-9964/11/10/503/pdf?version=1664444024","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1313176345","display_name":null,"funder_award_id":"41471318","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7550671205","display_name":null,"funder_award_id":"42201504","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4297540225.pdf","grobid_xml":"https://content.openalex.org/works/W4297540225.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1990784258","https://openalex.org/W2010621424","https://openalex.org/W2017250949","https://openalex.org/W2018587953","https://openalex.org/W2036798369","https://openalex.org/W2116098242","https://openalex.org/W2155706665","https://openalex.org/W2157026765","https://openalex.org/W2165577558","https://openalex.org/W2321905888","https://openalex.org/W2343614411","https://openalex.org/W2344031149","https://openalex.org/W2368444532","https://openalex.org/W2394035136","https://openalex.org/W2411392023","https://openalex.org/W2431738724","https://openalex.org/W2462353227","https://openalex.org/W2609825896","https://openalex.org/W2769491841","https://openalex.org/W2776163999","https://openalex.org/W2902422922","https://openalex.org/W2991954627","https://openalex.org/W3009942016","https://openalex.org/W3027225766","https://openalex.org/W3037640242","https://openalex.org/W3132926949","https://openalex.org/W3133726918","https://openalex.org/W3205399292","https://openalex.org/W6677599910","https://openalex.org/W6771093909"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W4375867731","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2015705630","https://openalex.org/W2355368334"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"deep":[3,32,69],"learning":[4,33],"has":[5],"become":[6],"the":[7,12,27,37,81,85,92,103,128,134,159,166,174,179],"mainstream":[8],"development":[9],"direction":[10],"in":[11,80],"change-detection":[13,28,58,86],"field,":[14],"and":[15,18,41,77,88,108,118,124,153,177],"its":[16,42],"accuracy":[17],"speed":[19],"have":[20],"also":[21],"reached":[22],"a":[23,68,141],"high":[24,63],"level.":[25],"However,":[26],"method":[29,167],"based":[30,66],"on":[31,67,102,158],"cannot":[34],"predict":[35],"all":[36],"change":[38],"areas":[39],"accurately,":[40],"application":[43],"is":[44,148],"limited":[45],"due":[46],"to":[47],"local":[48],"prediction":[49,93,175],"defects.":[50],"For":[51],"this":[52],"reason,":[53],"we":[54,139,154],"propose":[55,140],"an":[56],"interactive":[57],"network":[59,74],"(ICD)":[60],"for":[61,150],"very":[62],"resolution":[64],"(VHR)":[65],"convolution":[70],"neural":[71],"network.":[72,130],"The":[73,162],"integrates":[75],"positive-":[76],"negative-click":[78],"information":[79],"distance":[82],"layer":[83],"of":[84,137,143,168],"network,":[87],"users":[89],"can":[90,115,171],"correct":[91,173],"defects":[94,176],"by":[95],"adding":[96,111,169],"clicks.":[97],"We":[98],"carried":[99],"out":[100,156],"experiments":[101,157],"open":[104],"source":[105],"dataset":[106],"WHU":[107],"LEVIR-CD.":[109],"By":[110],"clicks,":[112,138,152],"their":[113],"F1-scores":[114],"reach":[116],"0.920":[117],"0.912,":[119],"respectively,":[120],"which":[121,147],"are":[122],"4.3%":[123],"4.2%":[125],"higher":[126],"than":[127],"original":[129],"To":[131],"better":[132],"evaluate":[133],"correction":[135],"ability":[136],"set":[142],"evaluation":[144],"indices\u2014click-correction":[145],"ranges,":[146],"suitable":[149],"evaluating":[151],"carry":[155],"above":[160],"models.":[161],"results":[163],"show":[164],"that":[165],"clicks":[170],"effectively":[172],"improve":[178],"result":[180],"accuracy.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2022-09-29T00:00:00"}