{"id":"https://openalex.org/W2969591647","doi":"https://doi.org/10.1109/siu.2019.8806533","title":"Optimization of Graph Affinity Matrix with Heuristic Methods in Dimensionality Reduction of Hypespectral Images","display_name":"Optimization of Graph Affinity Matrix with Heuristic Methods in Dimensionality Reduction of Hypespectral Images","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2969591647","doi":"https://doi.org/10.1109/siu.2019.8806533","mag":"2969591647"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2019.8806533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2019.8806533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-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/A5002263525","display_name":"O\u011fuzhan Ceylan","orcid":"https://orcid.org/0000-0002-0892-6380"},"institutions":[{"id":"https://openalex.org/I132286405","display_name":"Kadir Has University","ror":"https://ror.org/03zzckc47","country_code":"TR","type":"education","lineage":["https://openalex.org/I132286405"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"O\u011fuzhan Ceylan","raw_affiliation_strings":["Kadir Has &#x00DC;niversitesi, Y&#x00F6;netim Bili&#x015F;im Sistemleri, afadfm, dff"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kadir Has &#x00DC;niversitesi, Y&#x00F6;netim Bili&#x015F;im Sistemleri, afadfm, dff","institution_ids":["https://openalex.org/I132286405"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058660643","display_name":"G\u00fcl\u015fen Ta\u015fk\u0131n","orcid":"https://orcid.org/0000-0002-2294-4462"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Gulsen Taskin","raw_affiliation_strings":["&#x0130;stanbul Teknik &#x00DC;niversitesi","Istanbul Teknik Universitesi, Istanbul, TR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"&#x0130;stanbul Teknik &#x00DC;niversitesi","institution_ids":[]},{"raw_affiliation_string":"Istanbul Teknik Universitesi, Istanbul, TR","institution_ids":["https://openalex.org/I48912391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12925051,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9858999848365784,"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/T10057","display_name":"Face and Expression Recognition","score":0.982699990272522,"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/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5930063724517822},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5477052927017212},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5254893898963928},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.5203156471252441},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.4987771511077881},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49399763345718384},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.45740747451782227},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45652949810028076},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.45096686482429504},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44145408272743225},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41960638761520386},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40718746185302734},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3508606553077698},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.25838595628738403}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5930063724517822},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5477052927017212},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5254893898963928},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.5203156471252441},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.4987771511077881},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49399763345718384},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.45740747451782227},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45652949810028076},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.45096686482429504},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44145408272743225},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41960638761520386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40718746185302734},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3508606553077698},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.25838595628738403},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/siu.2019.8806533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2019.8806533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"},{"id":"pmh:oai:polen.itu.edu.tr:11527/62216","is_oa":false,"landing_page_url":"https://hdl.handle.net/11527/62216","pdf_url":null,"source":{"id":"https://openalex.org/S4306400460","display_name":"Istanbul Technical University Academic Open Archive (Istanbul Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48912391","host_organization_name":"Istanbul Technical University","host_organization_lineage":["https://openalex.org/I48912391"],"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":"Conference object"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1978775764","https://openalex.org/W1981791883","https://openalex.org/W1993885071","https://openalex.org/W2118439480","https://openalex.org/W2154872931","https://openalex.org/W2155985040","https://openalex.org/W2514028694","https://openalex.org/W2543580944","https://openalex.org/W2730849903","https://openalex.org/W2792584708"],"related_works":["https://openalex.org/W2292979300","https://openalex.org/W2137369096","https://openalex.org/W3000465807","https://openalex.org/W2014683590","https://openalex.org/W2351582470","https://openalex.org/W1980227981","https://openalex.org/W1984421104","https://openalex.org/W2512565647","https://openalex.org/W2001772920","https://openalex.org/W2393746448"],"abstract_inverted_index":{"Hyperspectral":[0],"images":[1,171],"include":[2],"hundreds":[3],"of":[4,9,54,63,84,102,130,138],"spectral":[5],"bands,":[6],"adjacent":[7],"ones":[8],"which":[10],"are":[11,40,89],"often":[12],"highly":[13],"correlated":[14],"and":[15,92,146,179],"noisy,":[16],"leading":[17],"to":[18,44,73,134],"a":[19,27,60,113,157,194],"decrease":[20],"in":[21,30,68,123,151],"classification":[22],"performance":[23,78,188],"as":[24,26],"well":[25],"high":[28,65,125],"increase":[29],"computational":[31],"time.":[32],"Dimensionality":[33],"reduction":[34],"techniques,":[35],"especially":[36,110],"the":[37,64,69,82,85,124,136,139,166,169,180,190],"nonlinear":[38],"ones,":[39],"very":[41,106],"effective":[42],"tools":[43],"solve":[45],"these":[46,103],"issues.":[47],"Locality":[48],"preserving":[49],"projection":[50],"(LPP)":[51],"is":[52,133],"one":[53],"those":[55],"graph":[56,152],"based":[57],"methods":[58,98],"providing":[59],"better":[61,176,187],"representation":[62],"dimensional":[66,126],"data":[67],"low-dimensional":[70],"space":[71],"compared":[72],"linear":[74],"methods.":[75],"However,":[76],"its":[77],"heavily":[79],"depends":[80],"on":[81,168],"parameters":[83,104,185],"affinity":[86,153],"matrix,":[87],"that":[88,173],"k-nearest":[90],"neighbor":[91],"heat":[93,115,159,181,191],"kernel":[94,182,192],"parameters.":[95],"Using":[96],"simple":[97],"like":[99],"grid-search,":[100],"optimization":[101,149,154],"becomes":[105],"computationally":[107],"demanding":[108],"process":[109],"when":[111],"considering":[112],"generalized":[114,158],"kernel,":[116],"including":[117,142],"an":[118],"exclusive":[119],"parameter":[120],"per":[121],"feature":[122],"space.":[127],"The":[128,161],"aim":[129],"this":[131],"paper":[132],"show":[135],"effectiveness":[137],"heuristic":[140],"methods,":[141],"harmony":[143],"search":[144],"(HS)":[145],"particle":[147],"swarm":[148],"(PSO),":[150],"constructed":[155],"with":[156,165,183,193],"kernel.":[160],"preliminary":[162],"results":[163],"obtained":[164],"experiments":[167],"hyperspectral":[170],"showed":[172],"HS":[174],"performs":[175],"than":[177,189],"PSO,":[178],"multiple":[184],"achieves":[186],"single":[195],"parameter.":[196]},"counts_by_year":[],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
