{"id":"https://openalex.org/W2807862495","doi":"https://doi.org/10.1109/tsmc.2018.2830099","title":"Efficient Deep CNN-Based Fire Detection and Localization in Video Surveillance Applications","display_name":"Efficient Deep CNN-Based Fire Detection and Localization in Video Surveillance Applications","publication_year":2018,"publication_date":"2018-06-14","ids":{"openalex":"https://openalex.org/W2807862495","doi":"https://doi.org/10.1109/tsmc.2018.2830099","mag":"2807862495"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2018.2830099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2018.2830099","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://researchonline.ljmu.ac.uk/id/eprint/8341/1/SMCA-17-10-1204-Final-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Khan Muhammad","orcid":"https://orcid.org/0000-0003-4055-7412"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Khan Muhammad","raw_affiliation_strings":["Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-4055-7412","affiliations":[{"raw_affiliation_string":"Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008903140","display_name":"Jamil Ahmad","orcid":"https://orcid.org/0000-0001-8407-5971"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jamil Ahmad","raw_affiliation_strings":["Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-8407-5971","affiliations":[{"raw_affiliation_string":"Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108044017","display_name":"Zhihan Lv","orcid":"https://orcid.org/0000-0003-2525-3074"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihan Lv","raw_affiliation_strings":["School of Data Science and Software Engineering, Qingdao University, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0003-2525-3074","affiliations":[{"raw_affiliation_string":"School of Data Science and Software Engineering, Qingdao University, Qingdao, China","institution_ids":["https://openalex.org/I108688024"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067123099","display_name":"Paolo Bellavista","orcid":"https://orcid.org/0000-0003-0992-7948"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Bellavista","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Bologna, Bologna, Italy"],"raw_orcid":"https://orcid.org/0000-0003-0992-7948","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Bologna, Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008276130","display_name":"Po Yang","orcid":"https://orcid.org/0000-0002-8553-7127"},"institutions":[{"id":"https://openalex.org/I63098007","display_name":"Liverpool John Moores University","ror":"https://ror.org/04zfme737","country_code":"GB","type":"education","lineage":["https://openalex.org/I63098007"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Po Yang","raw_affiliation_strings":["School of Computer Science, Liverpool John Moores University, Liverpool, U.K"],"raw_orcid":"https://orcid.org/0000-0002-8553-7127","affiliations":[{"raw_affiliation_string":"School of Computer Science, Liverpool John Moores University, Liverpool, U.K","institution_ids":["https://openalex.org/I63098007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072407810","display_name":"Sung Wook Baik","orcid":"https://orcid.org/0000-0002-6678-7788"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sung Wook Baik","raw_affiliation_strings":["Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-6678-7788","affiliations":[{"raw_affiliation_string":"Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":37.1785,"has_fulltext":true,"cited_by_count":522,"citation_normalized_percentile":{"value":0.99969639,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"49","issue":"7","first_page":"1419","last_page":"1434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":1.0,"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":1.0,"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":0.9957000017166138,"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.9567999839782715,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8174865245819092},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7995274662971497},{"id":"https://openalex.org/keywords/fire-detection","display_name":"Fire detection","score":0.7389389276504517},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6026294231414795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5892527103424072},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5607391595840454},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.47538721561431885},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41796499490737915},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3542923331260681},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3536912798881531},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3247828781604767},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08917310833930969},{"id":"https://openalex.org/keywords/architectural-engineering","display_name":"Architectural engineering","score":0.07895117998123169}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8174865245819092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7995274662971497},{"id":"https://openalex.org/C2780836893","wikidata":"https://www.wikidata.org/wiki/Q19922674","display_name":"Fire detection","level":2,"score":0.7389389276504517},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6026294231414795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5892527103424072},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5607391595840454},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.47538721561431885},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41796499490737915},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3542923331260681},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3536912798881531},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3247828781604767},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08917310833930969},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.07895117998123169},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tsmc.2018.2830099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2018.2830099","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"},{"id":"pmh:oai:researchonline.ljmu.ac.uk:8341","is_oa":true,"landing_page_url":null,"pdf_url":"https://researchonline.ljmu.ac.uk/id/eprint/8341/1/SMCA-17-10-1204-Final-3.pdf","source":{"id":"https://openalex.org/S4306401246","display_name":"Liverpool John Moores University","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63098007","host_organization_name":"Liverpool John Moores University","host_organization_lineage":["https://openalex.org/I63098007"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:cris.unibo.it:11585/729507","is_oa":true,"landing_page_url":"http://hdl.handle.net/11585/729507","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"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"}],"best_oa_location":{"id":"pmh:oai:researchonline.ljmu.ac.uk:8341","is_oa":true,"landing_page_url":null,"pdf_url":"https://researchonline.ljmu.ac.uk/id/eprint/8341/1/SMCA-17-10-1204-Final-3.pdf","source":{"id":"https://openalex.org/S4306401246","display_name":"Liverpool John Moores University","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63098007","host_organization_name":"Liverpool John Moores University","host_organization_lineage":["https://openalex.org/I63098007"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G8082801164","display_name":null,"funder_award_id":"2016R1A2B4011712","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2807862495.pdf","grobid_xml":"https://content.openalex.org/works/W2807862495.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W221912421","https://openalex.org/W1432470681","https://openalex.org/W1518544806","https://openalex.org/W1616262590","https://openalex.org/W1909366555","https://openalex.org/W1964084023","https://openalex.org/W1971256340","https://openalex.org/W1971301114","https://openalex.org/W1984282654","https://openalex.org/W1996199746","https://openalex.org/W2011160765","https://openalex.org/W2027645937","https://openalex.org/W2045169502","https://openalex.org/W2053186823","https://openalex.org/W2059704224","https://openalex.org/W2063975513","https://openalex.org/W2067779109","https://openalex.org/W2082526668","https://openalex.org/W2103941746","https://openalex.org/W2111586857","https://openalex.org/W2111692049","https://openalex.org/W2122856268","https://openalex.org/W2141277076","https://openalex.org/W2155893237","https://openalex.org/W2156734067","https://openalex.org/W2163605009","https://openalex.org/W2165698076","https://openalex.org/W2171201674","https://openalex.org/W2183182206","https://openalex.org/W2279098554","https://openalex.org/W2296583276","https://openalex.org/W2308630946","https://openalex.org/W2329582438","https://openalex.org/W2411063280","https://openalex.org/W2511413110","https://openalex.org/W2518658597","https://openalex.org/W2519284461","https://openalex.org/W2551235116","https://openalex.org/W2559767675","https://openalex.org/W2597086744","https://openalex.org/W2604541107","https://openalex.org/W2767690801","https://openalex.org/W2780222614","https://openalex.org/W2783430431","https://openalex.org/W2793947836","https://openalex.org/W3102431071","https://openalex.org/W3105270602","https://openalex.org/W3121847072","https://openalex.org/W4233493325","https://openalex.org/W4285719527","https://openalex.org/W6666605149","https://openalex.org/W6676849031","https://openalex.org/W6684191040","https://openalex.org/W6695314431","https://openalex.org/W6729905891"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W2949096641","https://openalex.org/W2969228573","https://openalex.org/W2970686063","https://openalex.org/W4320729701","https://openalex.org/W2963690996","https://openalex.org/W4254103348"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4],"yielded":[5],"state-of-the-art":[6],"performance":[7],"in":[8,18,52],"image":[9],"classification":[10],"and":[11,33,37,61,74,88,102,161,173],"other":[12],"computer":[13],"vision":[14],"tasks.":[15],"Their":[16],"application":[17],"fire":[19,31,46,85,158,177],"detection":[20,25,47,159],"systems":[21,48],"will":[22,28],"substantially":[23],"improve":[24],"accuracy,":[26],"which":[27,109],"eventually":[29],"minimize":[30],"disasters":[32],"reduce":[34],"the":[35,41,81,92,95,112,123,165,169,174],"ecological":[36],"social":[38],"ramifications.":[39],"However,":[40],"major":[42],"concern":[43],"with":[44],"CNN-based":[45],"is":[49],"their":[50,58],"implementation":[51],"real-world":[53],"surveillance":[54],"networks,":[55],"due":[56,142],"to":[57,115,136,143],"high":[59],"memory":[60],"computational":[62,113,121],"requirements":[63,114],"for":[64,84],"inference.":[65],"In":[66],"this":[67,148],"paper,":[68],"we":[69],"propose":[70],"an":[71],"original,":[72],"energy-friendly,":[73],"computationally":[75],"efficient":[76],"CNN":[77],"architecture,":[78],"inspired":[79],"by":[80,163],"SqueezeNet":[82],"architecture":[83],"detection,":[86],"localization,":[87],"semantic":[89],"understanding":[90],"of":[91,94,168,171,176],"scene":[93],"fire.":[96],"It":[97],"uses":[98],"smaller":[99],"convolutional":[100],"kernels":[101],"contains":[103],"no":[104],"dense,":[105],"fully":[106],"connected":[107],"layers,":[108],"helps":[110],"keep":[111],"a":[116,152],"minimum.":[117],"Despite":[118],"its":[119,144],"low":[120],"needs,":[122],"experimental":[124],"results":[125],"demonstrate":[126],"that":[127,133],"our":[128],"proposed":[129],"solution":[130],"achieves":[131],"accuracies":[132],"are":[134],"comparable":[135],"other,":[137],"more":[138],"complex":[139],"models,":[140],"mainly":[141],"increased":[145],"depth.":[146],"Moreover,":[147],"paper":[149],"shows":[150],"how":[151],"tradeoff":[153],"can":[154],"be":[155],"reached":[156],"between":[157],"accuracy":[160],"efficiency,":[162],"considering":[164],"specific":[166],"characteristics":[167],"problem":[170],"interest":[172],"variety":[175],"data.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":26},{"year":2025,"cited_by_count":62},{"year":2024,"cited_by_count":80},{"year":2023,"cited_by_count":104},{"year":2022,"cited_by_count":80},{"year":2021,"cited_by_count":70},{"year":2020,"cited_by_count":48},{"year":2019,"cited_by_count":45},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2018-06-21T00:00:00"}
