{"id":"https://openalex.org/W4288391575","doi":"https://doi.org/10.1109/access.2022.3194650","title":"Spectral-Spatial Classification of Hyperspectral Images Using BERT-Based Methods With HyperSLIC Segment Embeddings","display_name":"Spectral-Spatial Classification of Hyperspectral Images Using BERT-Based Methods With HyperSLIC Segment Embeddings","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4288391575","doi":"https://doi.org/10.1109/access.2022.3194650"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3194650","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3194650","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09843967.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/ielx7/6287639/6514899/09843967.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088753165","display_name":"Ibrahim Onur S\u0131\u011f\u0131rc\u0131","orcid":"https://orcid.org/0000-0002-6596-9635"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Ibrahim Onur Sigirci","raw_affiliation_strings":["Department of Computer Engineering, Yildiz Technical University (YTU), Davutpasa Campus, Istanbul, Turkey","Yildiz Technical University (YTU), Davutpasa Campus, Dpt. of Computer Engineering, 34220 Istanbul, Turkey and Signal and Image Processing Laboratory (SIMPLAB) at YTU, 34220 Istanbul, Turkey;"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yildiz Technical University (YTU), Davutpasa Campus, Istanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]},{"raw_affiliation_string":"Yildiz Technical University (YTU), Davutpasa Campus, Dpt. of Computer Engineering, 34220 Istanbul, Turkey and Signal and Image Processing Laboratory (SIMPLAB) at YTU, 34220 Istanbul, Turkey;","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082045666","display_name":"G\u00f6khan Bilgin","orcid":"https://orcid.org/0000-0002-5532-477X"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Gokhan Bilgin","raw_affiliation_strings":["Department of Computer Engineering, Yildiz Technical University (YTU), Davutpasa Campus, Istanbul, Turkey","Yildiz Technical University (YTU), Davutpasa Campus, Dpt. of Computer Engineering, 34220 Istanbul, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yildiz Technical University (YTU), Davutpasa Campus, Istanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]},{"raw_affiliation_string":"Yildiz Technical University (YTU), Davutpasa Campus, Dpt. of Computer Engineering, 34220 Istanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088753165"],"corresponding_institution_ids":["https://openalex.org/I4101805"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.904,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.76762189,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"10","issue":null,"first_page":"79152","last_page":"79164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9933000206947327,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9843000173568726,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8747586011886597},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6670879125595093},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5666956305503845},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5473811626434326},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34065765142440796}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8747586011886597},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6670879125595093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5666956305503845},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5473811626434326},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34065765142440796}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3194650","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3194650","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09843967.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:beeee3b66bfc4b24a3f539b93f16b489","is_oa":true,"landing_page_url":"https://doaj.org/article/beeee3b66bfc4b24a3f539b93f16b489","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 79152-79164 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3194650","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3194650","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09843967.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4169253990","display_name":null,"funder_award_id":"2014-04-01-KAP01","funder_id":"https://openalex.org/F4320323955","funder_display_name":"Yildiz Teknik \u00dcniversitesi"}],"funders":[{"id":"https://openalex.org/F4320323955","display_name":"Yildiz Teknik \u00dcniversitesi","ror":"https://ror.org/0547yzj13"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4288391575.pdf","grobid_xml":"https://content.openalex.org/works/W4288391575.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W206338564","https://openalex.org/W1521436688","https://openalex.org/W1522301498","https://openalex.org/W1939429412","https://openalex.org/W1972524915","https://openalex.org/W2029316659","https://openalex.org/W2032434887","https://openalex.org/W2047062858","https://openalex.org/W2067532478","https://openalex.org/W2085529604","https://openalex.org/W2101234009","https://openalex.org/W2104269704","https://openalex.org/W2114819256","https://openalex.org/W2118246710","https://openalex.org/W2126517171","https://openalex.org/W2131019926","https://openalex.org/W2136251662","https://openalex.org/W2142046002","https://openalex.org/W2152057649","https://openalex.org/W2152276863","https://openalex.org/W2153747028","https://openalex.org/W2159269332","https://openalex.org/W2164330327","https://openalex.org/W2168481151","https://openalex.org/W2168875522","https://openalex.org/W2179290474","https://openalex.org/W2500751094","https://openalex.org/W2600746131","https://openalex.org/W2609880332","https://openalex.org/W2611950832","https://openalex.org/W2777427437","https://openalex.org/W2791006446","https://openalex.org/W2799390666","https://openalex.org/W2809113079","https://openalex.org/W2896457183","https://openalex.org/W2902905019","https://openalex.org/W2963748441","https://openalex.org/W2971432438","https://openalex.org/W2996428491","https://openalex.org/W3046027728","https://openalex.org/W3122028341","https://openalex.org/W3122774149","https://openalex.org/W3128776197","https://openalex.org/W3134136658","https://openalex.org/W3135396862","https://openalex.org/W3214821343","https://openalex.org/W4210628037","https://openalex.org/W4214711995","https://openalex.org/W4240485910","https://openalex.org/W6608345076","https://openalex.org/W6631190155","https://openalex.org/W6675354045","https://openalex.org/W6713134421","https://openalex.org/W6737454330","https://openalex.org/W6755207826","https://openalex.org/W6768021236"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"The":[0,34,56,174],"classification":[1,181],"performance":[2],"is":[3,23,138,186,208],"highly":[4],"affected":[5],"because":[6],"hyperspectral":[7,136],"images":[8],"include":[9],"many":[10],"bands,":[11],"have":[12,16,48,102],"high":[13],"dimensions,":[14],"and":[15,30,59,170,197],"few":[17],"labeled":[18],"training":[19],"samples.":[20],"This":[21],"challenge":[22],"reduced":[24],"by":[25],"using":[26],"rich":[27],"spatial":[28,83,98,206],"information":[29,84,179,207],"an":[31],"effective":[32],"classifier.":[33],"classifiers":[35,204],"in":[36,52,93,106,145,183],"this":[37,146],"study":[38],"are":[39,69,90,153],"BERT-based":[40,143,184,193],"(Bidirectional":[41],"Encoder":[42],"Representations":[43],"from":[44],"Transformers)":[45],"models,":[46],"which":[47],"recently":[49],"been":[50],"applied":[51],"natural":[53],"language":[54],"processing.":[55],"BERT":[57],"model":[58],"its":[60],"performance-improved":[61],"version,":[62],"the":[63,94,107,112,117,122,131,156,164,211],"ALBERT":[64],"(A":[65],"Lite":[66],"BERT)":[67],"model,":[68],"utilized":[70],"as":[71,140,172],"transformer-based":[72],"models.":[73],"Because":[74],"of":[75,114,130,166,176,213],"their":[76],"structure,":[77],"these":[78],"models":[79,144,185,194],"can":[80],"also":[81],"accept":[82],"via":[85],"‘segment":[86],"embeddings’.":[87],"Segmentation":[88],"algorithms":[89],"commonly":[91],"used":[92,209],"literature":[95,109],"to":[96,111,142,162],"get":[97],"information.":[99,216],"Superpixel":[100],"methods":[101],"shown":[103],"superior":[104],"results":[105,152,190],"segmentation":[108,151],"due":[110],"utility":[113],"working":[115],"at":[116],"superpixel":[118,133],"level":[119],"rather":[120],"than":[121],"conventional":[123,196],"pixel":[124],"level.":[125],"HyperSLIC,":[126],"a":[127],"modified":[128],"version":[129],"SLIC":[132],"method":[134],"for":[135,159],"images,":[137],"employed":[139],"input":[141],"study.":[147],"In":[148],"addition,":[149],"HyperSLIC":[150],"merged":[154],"with":[155,210],"DBSCAN":[157],"algorithm":[158],"similar":[160,168],"superpixels":[161],"increase":[163],"size":[165],"spatially":[167],"areas":[169],"called":[171],"HyperSLIC-DBSCAN.":[173],"effects":[175],"segment":[177,214],"embedding":[178,215],"on":[180],"accuracy":[182],"studied":[187],"experimentally.":[188],"Experimental":[189],"show":[191],"that":[192],"outperform":[195],"deep":[198],"learning-based":[199],"1D/2D":[200],"convolutional":[201],"neural":[202],"network":[203],"when":[205],"help":[212]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}