{"id":"https://openalex.org/W4388893618","doi":"https://doi.org/10.1109/tencon58879.2023.10322355","title":"Fire Detection Using Level Set Segmentation Based Fractional Order Optical Flow and 4D Fire Features with Mixed Data CNN-LSTM Model","display_name":"Fire Detection Using Level Set Segmentation Based Fractional Order Optical Flow and 4D Fire Features with Mixed Data CNN-LSTM Model","publication_year":2023,"publication_date":"2023-10-31","ids":{"openalex":"https://openalex.org/W4388893618","doi":"https://doi.org/10.1109/tencon58879.2023.10322355"},"language":"en","primary_location":{"id":"doi:10.1109/tencon58879.2023.10322355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon58879.2023.10322355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2023 - 2023 IEEE Region 10 Conference (TENCON)","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/A5020170016","display_name":"Muzammil Khan","orcid":"https://orcid.org/0000-0003-1914-6520"},"institutions":[{"id":"https://openalex.org/I91277730","display_name":"Maulana Azad National Institute of Technology","ror":"https://ror.org/026vtd268","country_code":"IN","type":"education","lineage":["https://openalex.org/I91277730"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Muzammil Khan","raw_affiliation_strings":["Maulana Azad National Institute of Technology,Department of Mathematics, Bioinformatics and Computer Applications,Bhopal,India,462003"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Maulana Azad National Institute of Technology,Department of Mathematics, Bioinformatics and Computer Applications,Bhopal,India,462003","institution_ids":["https://openalex.org/I91277730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083931046","display_name":"Pushpendra Kumar","orcid":"https://orcid.org/0000-0002-4946-766X"},"institutions":[{"id":"https://openalex.org/I91277730","display_name":"Maulana Azad National Institute of Technology","ror":"https://ror.org/026vtd268","country_code":"IN","type":"education","lineage":["https://openalex.org/I91277730"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pushpendra Kumar","raw_affiliation_strings":["Maulana Azad National Institute of Technology,Department of Mathematics, Bioinformatics and Computer Applications,Bhopal,India,462003"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Maulana Azad National Institute of Technology,Department of Mathematics, Bioinformatics and Computer Applications,Bhopal,India,462003","institution_ids":["https://openalex.org/I91277730"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1888,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5075252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"152","last_page":"157"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9998999834060669,"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":0.9998999834060669,"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.9628000259399414,"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/computer-science","display_name":"Computer science","score":0.731170117855072},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6914381384849548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6652705669403076},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5525012612342834},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5175220966339111},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5015389919281006},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4990956783294678},{"id":"https://openalex.org/keywords/fire-detection","display_name":"Fire detection","score":0.4961901307106018},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4418856203556061},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4291940927505493},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.426466703414917},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39965537190437317},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.271313339471817},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16224166750907898},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12628057599067688}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.731170117855072},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6914381384849548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6652705669403076},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5525012612342834},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5175220966339111},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5015389919281006},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4990956783294678},{"id":"https://openalex.org/C2780836893","wikidata":"https://www.wikidata.org/wiki/Q19922674","display_name":"Fire detection","level":2,"score":0.4961901307106018},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4418856203556061},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4291940927505493},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.426466703414917},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39965537190437317},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.271313339471817},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16224166750907898},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12628057599067688},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":1,"locations":[{"id":"doi:10.1109/tencon58879.2023.10322355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon58879.2023.10322355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2023 - 2023 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G2194671929","display_name":null,"funder_award_id":"EEQ/2020/000154","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"},{"id":"https://openalex.org/G6597071763","display_name":null,"funder_award_id":"02011/24/2021","funder_id":"https://openalex.org/F4320323196","funder_display_name":"National Board for Higher Mathematics"}],"funders":[{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"},{"id":"https://openalex.org/F4320323196","display_name":"National Board for Higher Mathematics","ror":"https://ror.org/02m388s04"},{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W354163111","https://openalex.org/W1578285471","https://openalex.org/W2003495390","https://openalex.org/W2005089986","https://openalex.org/W2059704224","https://openalex.org/W2110674786","https://openalex.org/W2126926806","https://openalex.org/W2165734775","https://openalex.org/W2194775991","https://openalex.org/W2326399158","https://openalex.org/W2423020969","https://openalex.org/W2472920611","https://openalex.org/W2501359160","https://openalex.org/W2673629478","https://openalex.org/W3053427166","https://openalex.org/W3092356723","https://openalex.org/W3127528059","https://openalex.org/W3132971810","https://openalex.org/W3194796466","https://openalex.org/W4220822126","https://openalex.org/W4223958543","https://openalex.org/W4224273979","https://openalex.org/W4318816220","https://openalex.org/W4375827285"],"related_works":["https://openalex.org/W2358832620","https://openalex.org/W2381458399","https://openalex.org/W2023355163","https://openalex.org/W4386083130","https://openalex.org/W4392108774","https://openalex.org/W2069571255","https://openalex.org/W1972058229","https://openalex.org/W3111737715","https://openalex.org/W2103633652","https://openalex.org/W4248700453"],"abstract_inverted_index":{"As":[0],"we":[1],"are":[2,89,147,170],"aware":[3],"that":[4],"the":[5,58,69,74,78,97,108,154,179,187,205,215,221,224],"world":[6],"witnesses":[7],"a":[8,124,195,210,239],"huge":[9],"number":[10],"of":[11,20,37,52,60,68,83,115,209,223],"fire":[12,34,53,75,87,109,167,188],"breakouts":[13],"everyday,":[14],"which":[15,169],"results":[16],"in":[17,72,113,153,204],"high":[18],"numbers":[19],"hazardous":[21],"events":[22],"and":[23,28,47,80,94,182,214],"severe":[24],"losses":[25],"to":[26,149,164],"property":[27],"forest":[29],"vegetation.":[30],"Therefore,":[31],"early":[32,50],"stage":[33],"detection":[35,51,76,189],"is":[36,111,162,190,207,226,236],"vital":[38],"importance,":[39],"for":[40,101],"once":[41],"it":[42,44],"spreads":[43],"becomes":[45],"unmanageable":[46],"disastrous.":[48],"The":[49,66,85,157,200,232],"can":[54],"be":[55],"performed":[56,237],"with":[57,151,243],"help":[59],"vision":[61],"based":[62,131],"deep":[63],"learning":[64],"techniques.":[65],"novelty":[67],"work":[70,206],"lies":[71],"performing":[73],"using":[77,123],"static":[79,86],"dynamic":[81,98],"features":[82,88],"fire.":[84],"taken":[90],"as":[91,172],"shape,":[92],"texture,":[93],"color,":[95],"while":[96,143],"feature":[99],"accounts":[100],"its":[102],"flickering":[103],"motion.":[104],"For":[105],"this":[106],"purpose,":[107],"motion":[110,125,155],"estimated":[112,158],"terms":[114],"optical":[116,159],"flow":[117,141,160],"from":[118],"videos":[119],"(image":[120],"sequences)":[121],"by":[122,193],"edge":[126],"preserving":[127],"level":[128],"set":[129],"segmentation":[130],"fractional":[132,144],"order":[133,145],"variational":[134],"model.":[135,199],"Level":[136],"sets":[137],"provide":[138],"nicely":[139],"segmented":[140],"fields,":[142],"derivatives":[146],"capable":[148],"deal":[150],"discontinuities":[152],"field.":[156],"field":[161],"used":[163],"derive":[165],"four":[166],"features,":[168],"constituted":[171],"4D":[173,176,217],"vectors.":[174],"These":[175],"vectors":[177],"reduce":[178],"data":[180,197,202],"dimensionality":[181],"mitigates":[183],"over-fitting":[184],"problem.":[185],"Finally,":[186],"carried":[191],"out":[192],"implementing":[194],"mixed":[196,201],"CNN-LSTM":[198],"presented":[203],"composed":[208],"reference":[211],"image":[212],"frame":[213],"corresponding":[216],"vector":[218],"sequence.":[219],"Also,":[220],"significance":[222],"model":[225,233],"manifested":[227],"through":[228],"an":[229],"ablation":[230],"study.":[231],"performance":[234],"validation":[235],"thorough":[238],"comparison":[240],"study":[241],"conducted":[242],"several":[244],"existing":[245],"models.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}