{"id":"https://openalex.org/W4386160079","doi":"https://doi.org/10.1109/icarm58088.2023.10218951","title":"Research on Violence Detection Algorithm based on Multi-UAV","display_name":"Research on Violence Detection Algorithm based on Multi-UAV","publication_year":2023,"publication_date":"2023-07-08","ids":{"openalex":"https://openalex.org/W4386160079","doi":"https://doi.org/10.1109/icarm58088.2023.10218951"},"language":"en","primary_location":{"id":"doi:10.1109/icarm58088.2023.10218951","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icarm58088.2023.10218951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102748747","display_name":"Zhi-Qiang Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Zhu","raw_affiliation_strings":["School of Automation, Southeast University,Key Laboratory of Measurement and Control of CSE, Ministry of Education,Nanjing,China,210096"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University,Key Laboratory of Measurement and Control of CSE, Ministry of Education,Nanjing,China,210096","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010863275","display_name":"Xinde Li","orcid":"https://orcid.org/0000-0002-1529-4537"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinde Li","raw_affiliation_strings":["School of Automation, Southeast University,Key Laboratory of Measurement and Control of CSE, Ministry of Education,Nanjing,China,210096"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University,Key Laboratory of Measurement and Control of CSE, Ministry of Education,Nanjing,China,210096","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048113311","display_name":"Lianli Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lianli Zhu","raw_affiliation_strings":["China Coast Guard Academy,Research Center of China Coast Guard,Ningbo,Zhejiang,China,315801"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Coast Guard Academy,Research Center of China Coast Guard,Ningbo,Zhejiang,China,315801","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.436,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58779385,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"112111","issue":null,"first_page":"67","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9937999844551086,"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":0.9937000274658203,"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/computer-science","display_name":"Computer science","score":0.6816056966781616},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5649171471595764},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5395898222923279},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.523908257484436},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4598811864852905},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4569322466850281},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4413118064403534},{"id":"https://openalex.org/keywords/threshold-limit-value","display_name":"Threshold limit value","score":0.43011462688446045},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4108375310897827},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34037280082702637},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.28200632333755493},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15846508741378784}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6816056966781616},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5649171471595764},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5395898222923279},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.523908257484436},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4598811864852905},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4569322466850281},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4413118064403534},{"id":"https://openalex.org/C64413873","wikidata":"https://www.wikidata.org/wiki/Q21005","display_name":"Threshold limit value","level":2,"score":0.43011462688446045},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4108375310897827},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34037280082702637},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28200632333755493},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15846508741378784},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","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/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","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/icarm58088.2023.10218951","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icarm58088.2023.10218951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6100000143051147}],"awards":[{"id":"https://openalex.org/G594485248","display_name":null,"funder_award_id":"BE2020006,BE2020006-1","funder_id":"https://openalex.org/F4320327777","funder_display_name":"Jiangsu Provincial Key Research and Development Program"},{"id":"https://openalex.org/G7593628556","display_name":null,"funder_award_id":"62233003,62073072","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327777","display_name":"Jiangsu Provincial Key Research and Development Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W1550360051","https://openalex.org/W1932571874","https://openalex.org/W2024016554","https://openalex.org/W2029281799","https://openalex.org/W2141200610","https://openalex.org/W2169464261","https://openalex.org/W2534883251","https://openalex.org/W2601564443","https://openalex.org/W2605304682","https://openalex.org/W2884585870","https://openalex.org/W2962943250","https://openalex.org/W2963862187","https://openalex.org/W2997408160","https://openalex.org/W2997780656","https://openalex.org/W3034745255","https://openalex.org/W3127537865","https://openalex.org/W3160144088","https://openalex.org/W3173239828","https://openalex.org/W3184439416","https://openalex.org/W3207311111","https://openalex.org/W4306847871","https://openalex.org/W4313648520","https://openalex.org/W4317390895","https://openalex.org/W6632833404","https://openalex.org/W6640445177","https://openalex.org/W6753412334","https://openalex.org/W6798838024"],"related_works":["https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W4390494008","https://openalex.org/W2053596378","https://openalex.org/W2168523118","https://openalex.org/W2073639911","https://openalex.org/W2043988397"],"abstract_inverted_index":{"Based":[0],"on":[1,14,119],"the":[2,27,32,39,43,50,77,90,104,134,142,159,162,170,182,197,208,213],"30-meter":[3],"UAV":[4,129,202],"aerial":[5],"violence":[6,10,84,111,115,147,177],"data,":[7],"a":[8,97,224],"multi-UAV":[9,120],"detection":[11,16,85,116,148,176,178,183],"algorithm":[12,23,86,117,165,179],"based":[13,118],"target":[15,28],"is":[17,24,30,35,47,55,87,108,123,130,151,166,204,211,219],"proposed.":[18,88,124],"In":[19],"this":[20],"paper,":[21],"YOLOX":[22,164],"improved.":[25],"Because":[26],"pixel":[29],"small,":[31],"UFocus":[33],"module":[34,46,54],"designed":[36,56],"to":[37,57,140],"upsample":[38],"feature":[40],"image,":[41],"and":[42,66,71,133,136,153],"channel":[44],"attention":[45],"cascaded":[48,67],"after":[49],"UFocus.":[51],"The":[52,61,125,145,155,173],"DAM":[53,69],"improve":[58],"spatial":[59],"attention.":[60],"shallow":[62],"features":[63,73],"are":[64,74,138],"extracted":[65],"with":[68,76,185],"modules,":[70],"multi-scale":[72],"fused":[75,139],"deep":[78],"semantic":[79],"features.":[80],"A":[81,114],"dual-threshold":[82,105],"single-machine":[83],"When":[89,207],"number":[91],"of":[92,128,161,189,200,223],"violent":[93,98],"actions":[94],"detected":[95],"in":[96],"video":[99],"within":[100],"three":[101,192],"seconds":[102],"meets":[103],"constraint,":[106],"it":[107],"determined":[109],"that":[110,158,222],"has":[112],"occurred.":[113],"information":[121,203],"fusion":[122,199],"confidence":[126,135],"value":[127],"dynamically":[131],"allocated,":[132],"probability":[137,209],"obtain":[141],"comprehensive":[143],"results.":[144],"self-built":[146],"data":[149],"set":[150],"tested":[152],"trained.":[154],"experiment":[156],"shows":[157],"accuracy":[160,188,214],"improved":[163],"1.56%":[167],"higher":[168],"than":[169,221],"original":[171],"algorithm.":[172],"dual":[174],"threshold":[175,210],"can":[180],"complete":[181],"task,":[184],"an":[186,195],"average":[187],"71%.":[190],"Taking":[191],"UAVs":[193],"as":[194],"example,":[196],"weighted":[198],"multiple":[201],"carried":[205],"out.":[206],"0.6,":[212],"rate":[215],"reaches":[216],"89%,":[217],"which":[218],"25.4%higher":[220],"single":[225],"UAV.":[226]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
