{"id":"https://openalex.org/W4388017384","doi":"https://doi.org/10.1109/access.2023.3328388","title":"Graph-Based Semi-Supervised Learning With Tensor Embeddings for Hyperspectral Data Classification","display_name":"Graph-Based Semi-Supervised Learning With Tensor Embeddings for Hyperspectral Data Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388017384","doi":"https://doi.org/10.1109/access.2023.3328388"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3328388","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3328388","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10301611.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10301611.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076478937","display_name":"Ioannis Georgoulas","orcid":"https://orcid.org/0009-0005-8826-9112"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioannis Georgoulas","raw_affiliation_strings":["School of Rural and Surveying Engineering, National Technical University of Athens, Athens, Greece"],"raw_orcid":"https://orcid.org/0009-0005-8826-9112","affiliations":[{"raw_affiliation_string":"School of Rural and Surveying Engineering, National Technical University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039837405","display_name":"Eftychios Protopapadakis","orcid":"https://orcid.org/0000-0003-3876-0024"},"institutions":[{"id":"https://openalex.org/I192756129","display_name":"University of Macedonia","ror":"https://ror.org/05fg6gr82","country_code":"GR","type":"education","lineage":["https://openalex.org/I192756129"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Eftychios Protopapadakis","raw_affiliation_strings":["School of Information Sciences, University of Macedonia, Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0003-3876-0024","affiliations":[{"raw_affiliation_string":"School of Information Sciences, University of Macedonia, Thessaloniki, Greece","institution_ids":["https://openalex.org/I192756129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057445534","display_name":"Konstantinos Makantasis","orcid":"https://orcid.org/0000-0002-0889-2766"},"institutions":[{"id":"https://openalex.org/I197854408","display_name":"University of Malta","ror":"https://ror.org/03a62bv60","country_code":"MT","type":"education","lineage":["https://openalex.org/I197854408"]}],"countries":["MT"],"is_corresponding":false,"raw_author_name":"Konstantinos Makantasis","raw_affiliation_strings":["Department of Artificial Intelligence, University of Malta, Msida, Malta"],"raw_orcid":"https://orcid.org/0000-0002-0889-2766","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, University of Malta, Msida, Malta","institution_ids":["https://openalex.org/I197854408"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082718586","display_name":"Dylan Seychell","orcid":"https://orcid.org/0000-0002-2377-9833"},"institutions":[{"id":"https://openalex.org/I197854408","display_name":"University of Malta","ror":"https://ror.org/03a62bv60","country_code":"MT","type":"education","lineage":["https://openalex.org/I197854408"]}],"countries":["MT"],"is_corresponding":false,"raw_author_name":"Dylan Seychell","raw_affiliation_strings":["Department of Artificial Intelligence, University of Malta, Msida, Malta"],"raw_orcid":"https://orcid.org/0000-0002-2377-9833","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, University of Malta, Msida, Malta","institution_ids":["https://openalex.org/I197854408"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102914203","display_name":"Anastasios Doulamis","orcid":"https://orcid.org/0000-0002-0612-5889"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Anastasios Doulamis","raw_affiliation_strings":["School of Rural and Surveying Engineering, National Technical University of Athens, Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0002-0612-5889","affiliations":[{"raw_affiliation_string":"School of Rural and Surveying Engineering, National Technical University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033117805","display_name":"Nikolaos Doulamis","orcid":null},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikolaos Doulamis","raw_affiliation_strings":["School of Rural and Surveying Engineering, National Technical University of Athens, Athens, Greece"],"raw_orcid":"https://orcid.org/0000-0002-4064-8990","affiliations":[{"raw_affiliation_string":"School of Rural and Surveying Engineering, National Technical University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.44,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.81818182,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"11","issue":null,"first_page":"124819","last_page":"124832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9782000184059143,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.972599983215332,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8412631750106812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.650292694568634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6071878671646118},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.58027583360672},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5611875653266907},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.46874430775642395},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.44267767667770386},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35593295097351074},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23706430196762085},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.13027623295783997}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8412631750106812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.650292694568634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6071878671646118},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.58027583360672},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5611875653266907},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.46874430775642395},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.44267767667770386},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35593295097351074},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23706430196762085},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.13027623295783997},{"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:10.1109/access.2023.3328388","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3328388","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10301611.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:www.um.edu.mt:123456789/125870","is_oa":true,"landing_page_url":"https://www.um.edu.mt/library/oar/handle/123456789/125870","pdf_url":"https://www.um.edu.mt/library/oar/bitstream/123456789/125870/1/Graph%20based%20semi%20supervised%20learning%20with%20tensor%20embeddings%20for%20hyperspectral%20data%20classification%202023.pdf","source":{"id":"https://openalex.org/S4306400782","display_name":"OAR@UM (University of Malta)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I197854408","host_organization_name":"University of Malta","host_organization_lineage":["https://openalex.org/I197854408"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:9df9e7a8f16e429f91e204b0dec9bbae","is_oa":true,"landing_page_url":"https://doaj.org/article/9df9e7a8f16e429f91e204b0dec9bbae","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":"IEEE Access, Vol 11, Pp 124819-124832 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3328388","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3328388","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10301611.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2905680489","display_name":null,"funder_award_id":"871908","funder_id":"https://openalex.org/F4320337663","funder_display_name":"H2020 Industrial Leadership"},{"id":"https://openalex.org/G6888519810","display_name":null,"funder_award_id":"871908","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320337663","display_name":"H2020 Industrial Leadership","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388017384.pdf","grobid_xml":"https://content.openalex.org/works/W4388017384.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1585433513","https://openalex.org/W1630959083","https://openalex.org/W1966580635","https://openalex.org/W2169898291","https://openalex.org/W2604163838","https://openalex.org/W2625392636","https://openalex.org/W2759880437","https://openalex.org/W2766962042","https://openalex.org/W2768975974","https://openalex.org/W2788919449","https://openalex.org/W2885260938","https://openalex.org/W2901123978","https://openalex.org/W2914072416","https://openalex.org/W2970845903","https://openalex.org/W2984353870","https://openalex.org/W2986799142","https://openalex.org/W3008390932","https://openalex.org/W3106141888","https://openalex.org/W3120408851","https://openalex.org/W3123291413","https://openalex.org/W3133744637","https://openalex.org/W3138725786","https://openalex.org/W3153239684","https://openalex.org/W3186406830","https://openalex.org/W3213631637","https://openalex.org/W4205694852","https://openalex.org/W4224882649","https://openalex.org/W4281633835","https://openalex.org/W4291652931","https://openalex.org/W4293731866","https://openalex.org/W4313627848","https://openalex.org/W4324144346","https://openalex.org/W4385732594","https://openalex.org/W6636599907","https://openalex.org/W6682494755","https://openalex.org/W6739344841","https://openalex.org/W6749396741","https://openalex.org/W6779206375","https://openalex.org/W6784998633"],"related_works":["https://openalex.org/W2513638114","https://openalex.org/W4390062853","https://openalex.org/W2340127552","https://openalex.org/W4389256085","https://openalex.org/W3210156800","https://openalex.org/W2518241345","https://openalex.org/W3033485676","https://openalex.org/W3166049060","https://openalex.org/W4311865232","https://openalex.org/W2904380457"],"abstract_inverted_index":{"Hyperspectral":[0],"data":[1,58,91,130],"classification":[2,151],"is":[3,32,59,67,92],"one":[4],"of":[5,28,40,76,85,89,108,111,114,128,138],"the":[6,29,36,83,93,109,126,136,150],"fundamental":[7],"problems":[8],"in":[9,47],"remote":[10],"sensing.":[11],"Several":[12],"algorithms":[13,31],"based":[14],"on":[15,35],"supervised":[16],"machine":[17],"learning":[18,117,146],"have":[19],"been":[20],"proposed":[21,30],"to":[22,44,81],"address":[23],"it.":[24],"The":[25],"performance,":[26],"however,":[27,66],"inherently":[33],"dependent":[34],"amount":[37],"and":[38,50,71],"quality":[39],"annotated":[41,90],"data.":[42],"Due":[43],"recent":[45],"advances":[46],"hyperspectral":[48,57,129],"imaging":[49],"autonomous":[51],"(unmanned)":[52],"aerial":[53],"vehicles":[54],"collecting":[55],"new":[56],"an":[60],"easy":[61],"task.":[62],"Annotating":[63],"those":[64],"data,":[65],"a":[68,86,104,112],"tedious,":[69],"time-consuming":[70],"costly":[72],"task":[73],"requiring":[74],"thein-situpresence":[75],"human":[77,154],"experts.":[78],"One":[79],"way":[80],"loosen":[82],"requirement":[84],"large":[87],"number":[88],"shift":[94],"tosemi-supervised":[95],"learningcombined":[96],"with":[97,120,143],"highly":[98],"sample-efficienttensor-basedneural":[99],"networks.":[100],"This":[101],"study":[102],"provides":[103],"comprehensive":[105],"experimental":[106],"analysis":[107],"performance":[110],"variety":[113],"graph-based":[115,144],"semi-supervised":[116,145],"techniques":[118],"combined":[119],"tensor-based":[121,139],"neural":[122,140],"network":[123,141],"embeddings":[124,142],"for":[125],"problem":[127],"classification.":[131],"Experimental":[132],"results":[133,152],"suggest":[134],"that":[135],"combination":[137],"can":[147],"significantly":[148],"improve":[149],"minimizing":[153],"annotation":[155],"effort.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}