{"id":"https://openalex.org/W2589840226","doi":"https://doi.org/10.1109/lgrs.2017.2665679","title":"Semisupervised Hyperspectral Image Classification Using Small Sample Sizes","display_name":"Semisupervised Hyperspectral Image Classification Using Small Sample Sizes","publication_year":2017,"publication_date":"2017-02-23","ids":{"openalex":"https://openalex.org/W2589840226","doi":"https://doi.org/10.1109/lgrs.2017.2665679","mag":"2589840226"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2017.2665679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2017.2665679","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/A5102777246","display_name":"M. Said Aydemir","orcid":"https://orcid.org/0000-0002-0767-3430"},"institutions":[{"id":"https://openalex.org/I198068145","display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu","ror":"https://ror.org/04w9kkr77","country_code":"TR","type":"government","lineage":["https://openalex.org/I198068145"]},{"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":"Muhammet Said Aydemir","raw_affiliation_strings":["SIMPLAB, Yildiz Technical University, Istanbul, Turkey","The Scientific and Technological Research Council of Turkey, Kocaeli, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIMPLAB, Yildiz Technical University, Istanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]},{"raw_affiliation_string":"The Scientific and Technological Research Council of Turkey, Kocaeli, Turkey","institution_ids":["https://openalex.org/I198068145"]}]},{"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), Istanbul, Turkey"],"raw_orcid":"https://orcid.org/0000-0002-5532-477X","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yildiz Technical University (YTU), Istanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9825,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.94325116,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"14","issue":"5","first_page":"621","last_page":"625"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9733999967575073,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9660000205039978,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9211225509643555},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7252218127250671},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7058323621749878},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6892394423484802},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5580219626426697},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5558656454086304},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5371933579444885},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5364115834236145},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5030335783958435},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.48926207423210144},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4777361750602722},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.43545860052108765},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41956621408462524},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38518109917640686},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.2742866277694702},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24773266911506653}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9211225509643555},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7252218127250671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7058323621749878},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6892394423484802},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5580219626426697},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5558656454086304},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5371933579444885},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5364115834236145},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5030335783958435},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.48926207423210144},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4777361750602722},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.43545860052108765},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41956621408462524},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38518109917640686},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2742866277694702},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24773266911506653},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2017.2665679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2017.2665679","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.800000011920929,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1516724916","https://openalex.org/W1978074368","https://openalex.org/W1995299967","https://openalex.org/W1997565609","https://openalex.org/W2009286595","https://openalex.org/W2013441453","https://openalex.org/W2035413749","https://openalex.org/W2039077039","https://openalex.org/W2039286126","https://openalex.org/W2039562180","https://openalex.org/W2041478093","https://openalex.org/W2044822643","https://openalex.org/W2076414618","https://openalex.org/W2081014110","https://openalex.org/W2107131609","https://openalex.org/W2125799222","https://openalex.org/W2153409933","https://openalex.org/W2296398754","https://openalex.org/W2541076639","https://openalex.org/W2545637130","https://openalex.org/W6660162900"],"related_works":["https://openalex.org/W2901421464","https://openalex.org/W2900715739","https://openalex.org/W2289496068","https://openalex.org/W2043864454","https://openalex.org/W2547116720","https://openalex.org/W2188831877","https://openalex.org/W2157356416","https://openalex.org/W3125885229","https://openalex.org/W1483460610","https://openalex.org/W2828181497"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1,57],"classification":[2,38,58],"is":[3,33,40,60,75,100,130],"a":[4,9,53,63,85,117,127,157],"challenging":[5],"task":[6],"when":[7],"only":[8],"small":[10,158],"number":[11,159],"of":[12,46,69,72,78,104,119,160],"labeled":[13,48,81,162],"samples":[14,83,94],"are":[15],"available":[16],"due":[17],"to":[18,27,65],"the":[19,29,37,44,47,70,76,79,91,101,120,138,146],"difficult,":[20],"expensive,":[21],"and":[22,111,122,151],"time-consuming":[23],"ground":[24],"campaigns":[25],"required":[26],"collect":[28],"ground-truth":[30],"information.":[31],"It":[32],"also":[34,131],"known":[35],"that":[36,145],"performance":[39],"highly":[41],"dependent":[42],"on":[43],"size":[45],"data.":[49],"In":[50],"this":[51,73],"letter,":[52],"semisupervised":[54],"learning-based":[55],"hyperspectral":[56],"framework":[59,148],"proposed":[61,132,147],"as":[62],"solution":[64],"these":[66],"problems.":[67],"One":[68],"contributions":[71],"letter":[74],"selection":[77],"initial":[80,161],"training":[82],"with":[84],"subtractive":[86],"clustering-based":[87],"approach,":[88],"which":[89],"provides":[90],"most":[92],"informative":[93],"for":[95],"graph-based":[96],"self-training.":[97],"Another":[98],"contribution":[99],"decision-level":[102],"combination":[103,118],"results":[105],"obtained":[106],"by":[107,125],"support":[108],"vector":[109],"machines":[110],"kernel":[112],"sparse":[113],"representation":[114],"classifiers.":[115],"Additionally,":[116],"spatial":[121],"spectral":[123],"information":[124,136],"creating":[126],"window":[128],"structure":[129],"via":[133],"integrating":[134],"contextual":[135],"from":[137],"neighboring":[139],"pixels.":[140],"The":[141],"explanatory":[142],"experiments":[143],"confirm":[144],"offers":[149],"better":[150],"more":[152],"promising":[153],"results,":[154],"even":[155],"using":[156],"samples.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
