{"id":"https://openalex.org/W1996089534","doi":"https://doi.org/10.1109/siu.2013.6531547","title":"Compressive Sensing based flame detection in infrared videos","display_name":"Compressive Sensing based flame detection in infrared videos","publication_year":2013,"publication_date":"2013-04-01","ids":{"openalex":"https://openalex.org/W1996089534","doi":"https://doi.org/10.1109/siu.2013.6531547","mag":"1996089534"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2013.6531547","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2013.6531547","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 21st 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/A5033894508","display_name":"Osman G\u00fcnay","orcid":"https://orcid.org/0000-0001-7131-2253"},"institutions":[{"id":"https://openalex.org/I56303344","display_name":"Aselsan (Turkey)","ror":"https://ror.org/04knh8e66","country_code":"TR","type":"company","lineage":["https://openalex.org/I56303344"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"O. Gunay","raw_affiliation_strings":["M\u0130KES Mikrodalga Elektronik Sistemler Sanayi ve Ticaret A.\u015e, Ankara, Turkey","MIKES Mikrodalga Elektron. Sistemler Sanayi ve Ticaret A. S., Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"M\u0130KES Mikrodalga Elektronik Sistemler Sanayi ve Ticaret A.\u015e, Ankara, Turkey","institution_ids":["https://openalex.org/I56303344"]},{"raw_affiliation_string":"MIKES Mikrodalga Elektron. Sistemler Sanayi ve Ticaret A. S., Ankara, Turkey","institution_ids":["https://openalex.org/I56303344"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080469744","display_name":"Ahmet Enis \u00c7etin","orcid":"https://orcid.org/0000-0002-3449-1958"},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"A. E. Cetin","raw_affiliation_strings":["Elektrik ve Elektronik M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Bilkent \u00dcniversitesi, Ankara, Turkey","Elektrik Elektron. Muhendisligi Bolumu, Bilkent Univ., Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Elektrik ve Elektronik M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Bilkent \u00dcniversitesi, Ankara, Turkey","institution_ids":["https://openalex.org/I168864056"]},{"raw_affiliation_string":"Elektrik Elektron. Muhendisligi Bolumu, Bilkent Univ., Ankara, Turkey","institution_ids":["https://openalex.org/I168864056"]}]}],"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":3,"citation_normalized_percentile":{"value":0.10524601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"6492","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9966999888420105,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7049046158790588},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6883724927902222},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6309856176376343},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6086772084236145},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5818755626678467},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5728198289871216},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5665614604949951},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5454935431480408},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5244986414909363},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49545371532440186},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.46038272976875305},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.45849621295928955},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.45646965503692627},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4531753659248352},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.4376922845840454},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4135035276412964},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29109734296798706},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.07772105932235718},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07561469078063965}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7049046158790588},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6883724927902222},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6309856176376343},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6086772084236145},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5818755626678467},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5728198289871216},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5665614604949951},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5454935431480408},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5244986414909363},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49545371532440186},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.46038272976875305},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.45849621295928955},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.45646965503692627},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4531753659248352},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.4376922845840454},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4135035276412964},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29109734296798706},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.07772105932235718},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07561469078063965},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/siu.2013.6531547","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2013.6531547","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 21st Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.bilkent.edu.tr:11693/27993","is_oa":false,"landing_page_url":"http://hdl.handle.net/11693/27993","pdf_url":null,"source":{"id":"https://openalex.org/S4306400079","display_name":"Bilkent University Institutional Repository (Bilkent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I168864056","host_organization_name":"Bilkent University","host_organization_lineage":["https://openalex.org/I168864056"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2013 21st Signal Processing and Communications Applications Conference (SIU)","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1553738992","https://openalex.org/W1603750645","https://openalex.org/W1855383459","https://openalex.org/W1972058229","https://openalex.org/W2023427355","https://openalex.org/W2032210760","https://openalex.org/W2083978531","https://openalex.org/W2105854624","https://openalex.org/W2111586857","https://openalex.org/W2139916508","https://openalex.org/W2141463923","https://openalex.org/W2152330798","https://openalex.org/W2156734067","https://openalex.org/W2172871209","https://openalex.org/W2296616510","https://openalex.org/W2499720122","https://openalex.org/W4244952642","https://openalex.org/W4250955649","https://openalex.org/W6633321784","https://openalex.org/W6676849031","https://openalex.org/W6682344681"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W3039673966","https://openalex.org/W2358292267","https://openalex.org/W4293699968","https://openalex.org/W2002351707","https://openalex.org/W2077021924"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,93],"Compressive":[4,46],"Sensing":[5,47],"based":[6],"feature":[7,39,53,131,138],"extraction":[8],"algorithm":[9],"is":[10,48,73,90,100,114,160],"proposed":[11],"for":[12],"flame":[13],"detection":[14],"using":[15,135,142],"infrared":[16],"cameras.":[17],"First,":[18],"bright":[19,154],"and":[20,35,37,96,153,158],"moving":[21,152],"regions":[22,155],"in":[23,63,126],"videos":[24,29],"are":[25,30,41,57,108,133,140,156],"detected.":[26],"Then":[27],"the":[28,61,64,67,78,97,103,111,117,124,148],"divided":[31],"into":[32],"spatio-temporal":[33],"blocks":[34],"spatial":[36,52],"temporal":[38],"vectors":[40,132,139],"exctracted":[42],"from":[43,110,116],"these":[44],"blocks.":[45,129],"used":[49,101],"to":[50,76,86],"exctract":[51],"vectors.":[54],"Compressed":[55],"measurements":[56],"obtained":[58,109],"by":[59],"multiplying":[60],"pixels":[62],"block":[65],"with":[66],"sensing":[68,79,104],"matrix.":[69,80,105],"A":[70,81],"new":[71],"method":[72],"also":[74],"developed":[75],"generate":[77],"random":[82],"vector":[83,112],"generated":[84],"according":[85],"standard":[87],"Gaussian":[88],"distribution":[89],"passed":[91],"through":[92],"wavelet":[94],"transform":[95],"resulting":[98],"matrix":[99],"as":[102],"Temporal":[106,137],"features":[107],"that":[113],"formed":[115],"difference":[118],"of":[119,123,166],"mean":[120],"intensity":[121],"values":[122],"frames":[125],"two":[127],"neighboring":[128],"Spatial":[130],"classified":[134,141,157],"Adaboost.":[136],"hidden":[143],"Markov":[144],"models.":[145],"To":[146],"reduce":[147],"computational":[149],"cost":[150],"only":[151],"classification":[159],"performed":[161],"at":[162],"specified":[163],"intervals":[164],"instead":[165],"every":[167],"frame.":[168]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
