{"id":"https://openalex.org/W2901769385","doi":"https://doi.org/10.1109/igarss.2018.8518799","title":"Domain Adaptation for Large Scale Classification of Very High Resolution Satellite Images with Deep Convolutional Neural Networks","display_name":"Domain Adaptation for Large Scale Classification of Very High Resolution Satellite Images with Deep Convolutional Neural Networks","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901769385","doi":"https://doi.org/10.1109/igarss.2018.8518799","mag":"2901769385"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 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/A5074310987","display_name":"Tristan Postadjian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"T. Postadjian","raw_affiliation_strings":["LASTIG MATIS, Univ. Paris Est, Saint-Mande, France","MATIS - M\u00e9thodes d'Analyses pour le Traitement d'Images et la St\u00e9r\u00e9orestitution (2-4 avenue Pasteur, 94165 Saint-Mand\u00e9 cedex - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LASTIG MATIS, Univ. Paris Est, Saint-Mande, France","institution_ids":[]},{"raw_affiliation_string":"MATIS - M\u00e9thodes d'Analyses pour le Traitement d'Images et la St\u00e9r\u00e9orestitution (2-4 avenue Pasteur, 94165 Saint-Mand\u00e9 cedex - France)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033550914","display_name":"Arnaud Le Bris","orcid":"https://orcid.org/0000-0002-1450-9161"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. Le Bris","raw_affiliation_strings":["LASTIG MATIS, Univ. Paris Est, Saint-Mande, France","MATIS - M\u00e9thodes d'Analyses pour le Traitement d'Images et la St\u00e9r\u00e9orestitution (2-4 avenue Pasteur, 94165 Saint-Mand\u00e9 cedex - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LASTIG MATIS, Univ. Paris Est, Saint-Mande, France","institution_ids":[]},{"raw_affiliation_string":"MATIS - M\u00e9thodes d'Analyses pour le Traitement d'Images et la St\u00e9r\u00e9orestitution (2-4 avenue Pasteur, 94165 Saint-Mand\u00e9 cedex - France)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029896607","display_name":"Hichem Sahbi","orcid":"https://orcid.org/0000-0001-6813-9146"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"H. Sahbi","raw_affiliation_strings":["CNRS, LIP6 UPMC Sorbonne Universit\u00e9s, Paris, France","MLIA - Machine Learning and Information Access (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS, LIP6 UPMC Sorbonne Universit\u00e9s, Paris, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I39804081"]},{"raw_affiliation_string":"MLIA - Machine Learning and Information Access (France)","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105807320","display_name":"C. Malle","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"C. Malle","raw_affiliation_strings":["LASTIG MATIS, Univ. Paris Est, Saint-Mande, France","MATIS - M\u00e9thodes d'Analyses pour le Traitement d'Images et la St\u00e9r\u00e9orestitution (2-4 avenue Pasteur, 94165 Saint-Mand\u00e9 cedex - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LASTIG MATIS, Univ. Paris Est, Saint-Mande, France","institution_ids":[]},{"raw_affiliation_string":"MATIS - M\u00e9thodes d'Analyses pour le Traitement d'Images et la St\u00e9r\u00e9orestitution (2-4 avenue Pasteur, 94165 Saint-Mand\u00e9 cedex - France)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9365,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.87854711,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"55","issue":null,"first_page":"3623","last_page":"3626"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9968000054359436,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9591000080108643,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8050519227981567},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7561767101287842},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6636993885040283},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.563376784324646},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5571025609970093},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5361698865890503},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5341780185699463},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5199088454246521},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4947051703929901},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4935828447341919},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4894758462905884},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4758070409297943},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4502803087234497},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.4474197328090668},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42929667234420776},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.16730326414108276},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.15549129247665405},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14251026511192322},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.14148202538490295},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.06958070397377014}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8050519227981567},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7561767101287842},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6636993885040283},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.563376784324646},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5571025609970093},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5361698865890503},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5341780185699463},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5199088454246521},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4947051703929901},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4935828447341919},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4894758462905884},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4758070409297943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4502803087234497},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.4474197328090668},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42929667234420776},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.16730326414108276},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.15549129247665405},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14251026511192322},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.14148202538490295},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.06958070397377014},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"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":2,"locations":[{"id":"doi:10.1109/igarss.2018.8518799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-02325855v1","is_oa":false,"landing_page_url":"https://hal.science/hal-02325855","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2018, Valencia, Spain. pp.3623-3626, ⟨10.1109/IGARSS.2018.8518799⟩","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2165698076","https://openalex.org/W2283002322","https://openalex.org/W2488187315","https://openalex.org/W2581906016","https://openalex.org/W2620572990","https://openalex.org/W3105127913","https://openalex.org/W3154664134","https://openalex.org/W4288076010","https://openalex.org/W6786026892"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2952813363","https://openalex.org/W4360783045"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1],"of":[2,16,26,44,54,90,105,123,135],"remote":[3],"sensing":[4],"images":[5],"enables":[6],"in":[7,93,101,131],"particular":[8],"land-cover":[9,124],"map":[10],"generation":[11],"for":[12,32],"a":[13,94,121,132],"given":[14],"set":[15,104,122],"classes.":[17],"Very":[18,45],"recent":[19],"literature":[20],"has":[21],"shown":[22],"the":[23,42,88,102,127],"superior":[24],"performance":[25],"deep":[27],"convolutional":[28],"neural":[29],"networks":[30],"(DCNN)":[31],"many":[33],"tasks,":[34],"from":[35],"object":[36,59],"recognition":[37],"to":[38,67,111,118,140],"semantic":[39],"labelling,":[40],"including":[41],"classification":[43,70,116],"High":[46],"Resolution":[47],"(VHR)":[48],"satellite":[49],"images.":[50],"However,":[51],"while":[52],"plethora":[53],"works":[55],"aim":[56],"at":[57,72],"improving":[58],"delineation":[60],"on":[61],"geographically":[62],"restricted":[63],"areas,":[64],"few":[65],"tend":[66],"solve":[68],"this":[69,108],"task":[71],"very":[73],"large":[74,114],"scales.":[75],"New":[76],"issues":[77],"occur":[78],"such":[79],"as":[80],"intra-class":[81],"class":[82],"variability,":[83],"diachrony":[84],"between":[85],"surveys,":[86],"and":[87,117,137],"appearance":[89],"new":[91],"classes":[92],"specific":[95,133],"area,":[96],"that":[97],"do":[98],"not":[99],"exist":[100],"predefined":[103],"labels.":[106],"Therefore,":[107],"work":[109],"intends":[110],"(i)":[112],"perform":[113],"scale":[115],"(ii)":[119],"expand":[120],"classes,":[125],"using":[126],"off-the-shelf":[128],"model":[129],"learnt":[130],"area":[134],"interest":[136],"adapting":[138],"it":[139],"unseen":[141],"areas.":[142]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}