{"id":"https://openalex.org/W2289988498","doi":"https://doi.org/10.1109/lgrs.2015.2512999","title":"Three-Layer Convex Network for Domain Adaptation in Multitemporal VHR Images","display_name":"Three-Layer Convex Network for Domain Adaptation in Multitemporal VHR Images","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2289988498","doi":"https://doi.org/10.1109/lgrs.2015.2512999","mag":"2289988498"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2015.2512999","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2512999","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5090812187","display_name":"Esam Othman","orcid":null},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Esam Othman","raw_affiliation_strings":["ALISR Laboratory, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"ALISR Laboratory, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054237841","display_name":"Yakoub Bazi","orcid":"https://orcid.org/0000-0001-9287-0596"},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Yakoub Bazi","raw_affiliation_strings":["ALISR Laboratory, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"ALISR Laboratory, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052594698","display_name":"Naif Alajlan","orcid":"https://orcid.org/0000-0003-1846-1131"},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Naif Alajlan","raw_affiliation_strings":["ALISR Laboratory, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"ALISR Laboratory, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030617821","display_name":"Haikel Alhichri","orcid":"https://orcid.org/0000-0003-2164-043X"},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Haikel AlHichri","raw_affiliation_strings":["ALISR Laboratory, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"ALISR Laboratory, Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021389231","display_name":"Farid Melgani","orcid":"https://orcid.org/0000-0001-9745-3732"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Farid Melgani","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5090812187"],"corresponding_institution_ids":["https://openalex.org/I28022161"],"apc_list":null,"apc_paid":null,"fwci":3.1105,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.92778716,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998000264167786,"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/T12676","display_name":"Machine Learning and ELM","score":0.9998000264167786,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/computer-science","display_name":"Computer science","score":0.7628062963485718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6602414846420288},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.554749608039856},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.46772730350494385},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4308333694934845},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4203639626502991},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.41614723205566406},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34169256687164307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7628062963485718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6602414846420288},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.554749608039856},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.46772730350494385},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4308333694934845},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4203639626502991},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.41614723205566406},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34169256687164307}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lgrs.2015.2512999","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2512999","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"},{"id":"pmh:oai:iris.unitn.it:11572/154233","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/154233","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5},{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4699999988079071}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335726","display_name":"Deanship of Scientific Research, King Saud University","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1997025799","https://openalex.org/W2024886312","https://openalex.org/W2026131661","https://openalex.org/W2042873848","https://openalex.org/W2060173047","https://openalex.org/W2085269372","https://openalex.org/W2115403315","https://openalex.org/W2149466042","https://openalex.org/W2151103935","https://openalex.org/W2163922914","https://openalex.org/W6681637710"],"related_works":["https://openalex.org/W2095030957","https://openalex.org/W2066827917","https://openalex.org/W2601157893","https://openalex.org/W2131735617","https://openalex.org/W2373006798","https://openalex.org/W2056912418","https://openalex.org/W2123759770","https://openalex.org/W2151520854","https://openalex.org/W2033213769","https://openalex.org/W2811390910"],"abstract_inverted_index":{"In":[0,94,154,176,200],"this":[1],"letter,":[2],"we":[3,98,143,157,180,203],"propose":[4],"a":[5,42,74,105],"novel":[6],"three-layer":[7],"convex":[8,86],"network":[9,47,84,184],"termed":[10],"as":[11,73],"3CN":[12,25,127],"for":[13],"domain":[14,40],"adaptation":[15],"in":[16,140,163],"multitemporal":[17],"very":[18],"high":[19],"resolution":[20],"(VHR)":[21],"remote":[22],"sensing":[23],"images.":[24,117],"is":[26,85],"composed":[27],"of":[28,107,126,209,217],"three":[29,89],"main":[30],"layers:":[31],"1)":[32],"mapping":[33],"source":[34,114,132,198],"training":[35,133,147],"samples":[36,134],"to":[37,103,128,135,149,167,185],"the":[38,65,70,95,131,136,145,151,159,164,177,183,192,195,201,207,210],"target":[39,54,71,116,137,152,165,196],"via":[41,57,64],"special":[43],"single-layer":[44],"feedforward":[45],"neural":[46],"called":[48,111],"extreme":[49],"learning":[50],"machine":[51],"(ELM);":[52],"2)":[53],"image":[55,72,166,219],"classification":[56,174],"ELM":[58],"too;":[59],"and":[60,77,115,170,190,197,205,224],"3)":[61],"spatial":[62,160],"regularization":[63],"random-walker":[66],"algorithm,":[67],"which":[68],"models":[69],"lattice":[75],"graph":[76],"then":[78],"minimizes":[79],"an":[80,172],"energy":[81],"functional.":[82],"This":[83],"because":[87],"all":[88],"layers":[90],"have":[91],"closed-form":[92],"solutions.":[93],"preprocessing":[96],"step,":[97,179],"use":[99,144],"scale-invariant":[100],"feature":[101],"transform":[102],"extract":[104],"set":[106,148],"matching":[108],"key":[109],"points":[110],"inliers":[112,120],"from":[113],"Then,":[118],"these":[119],"are":[121],"used":[122],"by":[123,222],"layer":[124,141,155],"1":[125],"spectrally":[129],"map":[130],"domain.":[138],"Next,":[139],"2,":[142],"mapped":[146],"classify":[150],"image.":[153],"3,":[156],"exploit":[158],"contextual":[161],"information":[162],"reduce":[168,191],"noise":[169],"generate":[171],"improved":[173],"map.":[175],"final":[178],"iteratively":[181],"fine-tune":[182],"increase":[186],"its":[187],"discrimination":[188],"ability":[189],"shift":[193],"between":[194],"domains.":[199],"experiments,":[202],"report":[204],"discuss":[206],"results":[208],"proposed":[211],"method":[212],"on":[213],"two":[214],"data":[215],"sets":[216],"VHR":[218],"pairs":[220],"acquired":[221],"IKONOS-2":[223],"GeoEye-1.":[225]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
