{"id":"https://openalex.org/W2979811751","doi":"https://doi.org/10.1109/multi-temp.2019.8866913","title":"Multi-temporal Change Detection based on Deep Semantic Segmentation Networks","display_name":"Multi-temporal Change Detection based on Deep Semantic Segmentation Networks","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2979811751","doi":"https://doi.org/10.1109/multi-temp.2019.8866913","mag":"2979811751"},"language":"en","primary_location":{"id":"doi:10.1109/multi-temp.2019.8866913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/multi-temp.2019.8866913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp)","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/A5054455922","display_name":"Lingxiang Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingxiang Lan","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103200805","display_name":"Dong Wu","orcid":"https://orcid.org/0000-0002-2306-5769"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Wu","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057267422","display_name":"Mingmin Chi","orcid":"https://orcid.org/0000-0003-2650-4146"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingmin Chi","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9409999847412109,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9280999898910522,"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":0.8177036046981812},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7856977581977844},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.7369034290313721},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6822757124900818},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6488016843795776},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5568486452102661},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5041192770004272},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4996955394744873},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4801856279373169}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8177036046981812},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7856977581977844},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.7369034290313721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6822757124900818},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6488016843795776},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5568486452102661},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5041192770004272},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4996955394744873},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4801856279373169},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/multi-temp.2019.8866913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/multi-temp.2019.8866913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1499255288","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2049585214","https://openalex.org/W2138957397","https://openalex.org/W2163605009","https://openalex.org/W2516616494","https://openalex.org/W2792827505","https://openalex.org/W2805152403","https://openalex.org/W2891248708","https://openalex.org/W2963881378","https://openalex.org/W3010257550","https://openalex.org/W3102127038","https://openalex.org/W6629944422","https://openalex.org/W6680396984","https://openalex.org/W6684191040","https://openalex.org/W6754663522"],"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/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2085033728","https://openalex.org/W3112772842","https://openalex.org/W1522196789"],"abstract_inverted_index":{"The":[0],"task":[1],"of":[2,47,55],"change":[3,30],"detection":[4,31],"(CD)":[5],"can":[6,15,64],"be":[7,16],"considered":[8],"as":[9],"a":[10,19,35,66],"pixel-level":[11],"classification":[12],"problem":[13],"and":[14],"fulfilled":[17],"by":[18],"semantic":[20,37],"segmentation":[21,38],"task.":[22],"In":[23],"this":[24],"paper,":[25],"we":[26],"propose":[27],"an":[28],"end-to-end":[29],"framework":[32,63],"based":[33],"on":[34,69],"deep":[36],"network,":[39],"in":[40,45],"particular,":[41],"fully":[42],"convolutional":[43],"networks":[44],"terms":[46],"the":[48,52,70],"difference":[49],"image":[50],"or":[51],"concatenated":[53],"one":[54],"multi-temporal":[56],"images.":[57],"Experimental":[58],"results":[59],"illustrate":[60],"that":[61],"our":[62],"obtain":[65],"state-of-the-art":[67],"result":[68],"real-world":[71],"high":[72],"resolution":[73],"CD":[74],"dataset.":[75]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}