{"id":"https://openalex.org/W4405786577","doi":"https://doi.org/10.1109/iros58592.2024.10801629","title":"Streamlining Forest Wildfire Surveillance: AI-Enhanced UAVs Utilizing the FLAME Aerial Video Dataset for Lightweight and Efficient Monitoring","display_name":"Streamlining Forest Wildfire Surveillance: AI-Enhanced UAVs Utilizing the FLAME Aerial Video Dataset for Lightweight and Efficient Monitoring","publication_year":2024,"publication_date":"2024-10-14","ids":{"openalex":"https://openalex.org/W4405786577","doi":"https://doi.org/10.1109/iros58592.2024.10801629"},"language":"en","primary_location":{"id":"doi:10.1109/iros58592.2024.10801629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10801629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5114236219","display_name":"Lemeng Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lemeng Zhao","raw_affiliation_strings":["Renmin University of China,Center for Applied Statistics and School of Statistics,Beijing,China,100872"],"affiliations":[{"raw_affiliation_string":"Renmin University of China,Center for Applied Statistics and School of Statistics,Beijing,China,100872","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085263462","display_name":"Junjie Hu","orcid":"https://orcid.org/0000-0002-1911-4361"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Hu","raw_affiliation_strings":["The Chinese University of Hong Kong,Shenzhen,China,518129"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Shenzhen,China,518129","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114236220","display_name":"Jianchao Bi","orcid":null},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianchao Bi","raw_affiliation_strings":["Renmin University of China,Gaoling School of Artificial Intelligence,Beijing,China,100872"],"affiliations":[{"raw_affiliation_string":"Renmin University of China,Gaoling School of Artificial Intelligence,Beijing,China,100872","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030356903","display_name":"Yanbing Bai","orcid":"https://orcid.org/0000-0001-5223-9425"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanbing Bai","raw_affiliation_strings":["Renmin University of China,Center for Applied Statistics and School of Statistics,Beijing,China,100872"],"affiliations":[{"raw_affiliation_string":"Renmin University of China,Center for Applied Statistics and School of Statistics,Beijing,China,100872","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016919969","display_name":"Erick Mas","orcid":"https://orcid.org/0000-0002-4861-5739"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Erick Mas","raw_affiliation_strings":["Tohoku University,International Research Institute of Disaster Science (IRIDeS),Sendai,Japan,980-8572"],"affiliations":[{"raw_affiliation_string":"Tohoku University,International Research Institute of Disaster Science (IRIDeS),Sendai,Japan,980-8572","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080104770","display_name":"Shunichi Koshimura","orcid":"https://orcid.org/0000-0002-8352-0639"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shunichi Koshimura","raw_affiliation_strings":["Tohoku University,International Research Institute of Disaster Science (IRIDeS),Sendai,Japan,980-8572"],"affiliations":[{"raw_affiliation_string":"Tohoku University,International Research Institute of Disaster Science (IRIDeS),Sendai,Japan,980-8572","institution_ids":["https://openalex.org/I201537933"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5114236219"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":0.2173,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53134336,"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":"8063","last_page":"8068"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10555","display_name":"Fire effects on ecosystems","score":0.9307000041007996,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.587115466594696},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.544017493724823},{"id":"https://openalex.org/keywords/aerial-survey","display_name":"Aerial survey","score":0.530136227607727},{"id":"https://openalex.org/keywords/video-monitoring","display_name":"Video monitoring","score":0.5006058216094971},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3959493339061737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3535088300704956},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.2662630081176758},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15606409311294556}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.587115466594696},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.544017493724823},{"id":"https://openalex.org/C176262533","wikidata":"https://www.wikidata.org/wiki/Q4688034","display_name":"Aerial survey","level":2,"score":0.530136227607727},{"id":"https://openalex.org/C3018537244","wikidata":"https://www.wikidata.org/wiki/Q242256","display_name":"Video monitoring","level":2,"score":0.5006058216094971},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3959493339061737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3535088300704956},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2662630081176758},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15606409311294556}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros58592.2024.10801629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10801629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2126579184","https://openalex.org/W2945697405","https://openalex.org/W2963321993","https://openalex.org/W2963526497","https://openalex.org/W2981304952","https://openalex.org/W2990152177","https://openalex.org/W3004505825","https://openalex.org/W3034658206","https://openalex.org/W3038510778","https://openalex.org/W3107849462","https://openalex.org/W3136217325","https://openalex.org/W3156973125","https://openalex.org/W3177141386","https://openalex.org/W3194085935","https://openalex.org/W3194477422","https://openalex.org/W3196908521","https://openalex.org/W3200405915","https://openalex.org/W3203618782","https://openalex.org/W3208367865","https://openalex.org/W3215212988","https://openalex.org/W4211057462","https://openalex.org/W4224952733","https://openalex.org/W4307823382","https://openalex.org/W4313171043","https://openalex.org/W6729448088","https://openalex.org/W6789558952","https://openalex.org/W6850060143","https://openalex.org/W6868797685"],"related_works":["https://openalex.org/W2121524756","https://openalex.org/W782553550","https://openalex.org/W1987967678","https://openalex.org/W2633218168","https://openalex.org/W4235897794","https://openalex.org/W2059707233","https://openalex.org/W1983126463","https://openalex.org/W2085738998","https://openalex.org/W2095126257","https://openalex.org/W2031511989"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"unmanned":[3],"aerial":[4,21,61],"vehicles":[5],"(UAVs)":[6],"have":[7],"played":[8],"an":[9],"increasingly":[10],"crucial":[11],"role":[12],"in":[13,49,97],"supporting":[14],"disaster":[15,50],"emergency":[16],"response":[17,51],"efforts":[18],"by":[19,124,132],"analyzing":[20],"images.":[22],"While":[23],"current":[24],"deep-learning":[25],"models":[26,152],"focus":[27],"on":[28,157],"improving":[29,130],"accuracy,":[30],"they":[31],"often":[32],"overlook":[33],"the":[34,43,70,87,98,111,117,143,146,163,167],"limited":[35],"computing":[36],"resources":[37],"of":[38,89],"UAVs.":[39],"This":[40,148],"study":[41],"recognizes":[42],"imperative":[44],"for":[45,60],"real-time":[46],"data":[47],"processing":[48],"scenarios":[52],"and":[53,57,75],"introduces":[54],"a":[55,90,158],"lightweight":[56],"efficient":[58],"approach":[59,120],"video":[62,71],"understanding.":[63],"Our":[64],"methodology":[65],"identifies":[66],"redundant":[67],"portions":[68],"within":[69],"through":[72],"policy":[73,100],"networks":[74],"eliminates":[76],"this":[77],"excess":[78],"information":[79,96],"using":[80],"frame":[81],"compression":[82],"techniques.":[83],"Additionally,":[84],"we":[85,109],"introduced":[86],"concept":[88],"station":[91],"point,":[92],"which":[93],"leverages":[94],"future":[95],"sequential":[99],"network,":[101],"thereby":[102],"enhancing":[103],"accuracy.":[104],"To":[105],"validate":[106],"our":[107,119,135],"method,":[108],"employed":[110],"wildfire":[112],"FLAME":[113],"dataset.":[114,147],"Compared":[115],"to":[116,153],"baseline,":[118],"reduces":[121],"computation":[122],"costs":[123],"more":[125],"than":[126],"10":[127],"times":[128],"while":[129],"accuracy":[131],"3%.":[133],"Moreover,":[134],"method":[136],"can":[137],"intelligently":[138],"select":[139],"salient":[140],"frames":[141],"from":[142],"video,":[144],"refining":[145],"feature":[149],"enables":[150],"sophisticated":[151],"be":[154],"effectively":[155],"trained":[156],"smaller":[159],"dataset,":[160],"significantly":[161],"reducing":[162],"time":[164],"spent":[165],"during":[166],"training":[168],"process.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}