{"id":"https://openalex.org/W4391582522","doi":"https://doi.org/10.1109/access.2024.3362958","title":"YOLO-Fall: A Novel Convolutional Neural Network Model for Fall Detection in Open Spaces","display_name":"YOLO-Fall: A Novel Convolutional Neural Network Model for Fall Detection in Open Spaces","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4391582522","doi":"https://doi.org/10.1109/access.2024.3362958"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3362958","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3362958","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10423005.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10423005.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101683081","display_name":"Deao Zhao","orcid":"https://orcid.org/0009-0004-0957-3339"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Deao Zhao","raw_affiliation_strings":["School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038663082","display_name":"T. Z. Song","orcid":"https://orcid.org/0000-0001-7710-8827"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Song","raw_affiliation_strings":["School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073887901","display_name":"Jie Gao","orcid":"https://orcid.org/0000-0001-9579-1703"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Gao","raw_affiliation_strings":["School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407434","display_name":"Dong Li","orcid":"https://orcid.org/0000-0002-3758-7218"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong Li","raw_affiliation_strings":["CNOOC Tianjin Chemical Research and Design Institute Ltd., Tianjin, China"],"affiliations":[{"raw_affiliation_string":"CNOOC Tianjin Chemical Research and Design Institute Ltd., Tianjin, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090027536","display_name":"Yuchen Niu","orcid":"https://orcid.org/0009-0007-9719-7549"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuchen Niu","raw_affiliation_strings":["School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101683081"],"corresponding_institution_ids":["https://openalex.org/I184843921"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.4996,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.97489657,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"12","issue":null,"first_page":"26137","last_page":"26149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9984999895095825,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9929999709129333,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9918000102043152,"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":0.7450847625732422},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7110240459442139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4233074188232422}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7450847625732422},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7110240459442139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4233074188232422}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3362958","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3362958","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10423005.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4929437d3bea4eac80fc6316df54d1f1","is_oa":true,"landing_page_url":"https://doaj.org/article/4929437d3bea4eac80fc6316df54d1f1","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 26137-26149 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3362958","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3362958","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10423005.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391582522.pdf","grobid_xml":"https://content.openalex.org/works/W4391582522.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2074099390","https://openalex.org/W2298290645","https://openalex.org/W2323017349","https://openalex.org/W2531409750","https://openalex.org/W2738593047","https://openalex.org/W2771763340","https://openalex.org/W2804771212","https://openalex.org/W2889508143","https://openalex.org/W2899006445","https://openalex.org/W2963420686","https://openalex.org/W3018757597","https://openalex.org/W3034502973","https://openalex.org/W3049494088","https://openalex.org/W3081597052","https://openalex.org/W3083408317","https://openalex.org/W3115362623","https://openalex.org/W3162418282","https://openalex.org/W3164612304","https://openalex.org/W3171038842","https://openalex.org/W3177052299","https://openalex.org/W3199218223","https://openalex.org/W4281679836","https://openalex.org/W4289752563","https://openalex.org/W4293584584","https://openalex.org/W4296143945","https://openalex.org/W4327517965","https://openalex.org/W4382775510","https://openalex.org/W4386076325","https://openalex.org/W6682137061","https://openalex.org/W6750227808","https://openalex.org/W6796223860","https://openalex.org/W6838598217"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Currently,":[0],"incidents":[1],"of":[2,14,27,43,120,161],"personal":[3],"accidents":[4],"occur":[5],"frequently":[6],"in":[7,125,131,153,179],"industrial":[8],"fields,":[9],"and":[10,61,104,122,137,204,222],"falling":[11],"is":[12,130],"one":[13],"the":[15,38,44,91,101,110,118,126,149,154,162,165,170,180,183],"most":[16,42],"common":[17],"safety":[18],"hazards.":[19],"This":[20,107],"makes":[21],"fall":[22,33,46,88],"detection":[23,47,56,213],"a":[24,94],"research":[25],"area":[26],"significant":[28],"importance.":[29],"Timely":[30],"responses":[31],"to":[32,67,133,196,211],"events":[34],"can":[35],"significantly":[36],"reduce":[37,134],"harm":[39],"caused.":[40],"However,":[41],"available":[45],"models":[48],"often":[49],"suffer":[50],"from":[51,174],"issues":[52],"such":[53],"as":[54],"insufficient":[55],"accuracy":[57],"or":[58,177],"high":[59],"parameter":[60],"computational":[62,138,205],"requirements,":[63],"making":[64,140],"them":[65],"challenging":[66],"deploy":[68],"on":[69,100],"local":[70],"devices.":[71],"In":[72,209],"response,":[73],"this":[74],"paper":[75,92],"introduces":[76],"an":[77],"enhanced":[78],"convolutional":[79],"neural":[80],"network":[81],"model,":[82],"YOLOv7-fall,":[83],"aimed":[84],"at":[85],"promptly":[86],"detecting":[87,115],"incidents.":[89],"Firstly,":[90],"proposes":[93],"novel":[95],"attention":[96],"module,":[97],"SDI,":[98],"based":[99],"Coordinate":[102],"Attention":[103],"Shuffle":[105],"Attention.":[106],"module":[108,160],"enhances":[109],"feature":[111],"extraction":[112],"capabilities":[113],"for":[114,144],"targets.":[116],"Secondly,":[117],"inclusion":[119],"GSConv":[121],"VoV-GSCSP":[123],"modules":[124],"model\u2019s":[127],"head":[128],"section":[129],"order":[132],"model":[135,171,200],"parameters":[136,201],"complexity,":[139],"it":[141],"more":[142,220],"suitable":[143],"deployment.":[145],"Thirdly,":[146],"by":[147,193,202,207],"replacing":[148],"conventional":[150],"3x3":[151],"convolution":[152],"final":[155],"ELAN(Efficient":[156],"Layer":[157],"Aggregation":[158],"Networks)":[159],"Backbone":[163],"with":[164],"DBB":[166],"(Diverse":[167],"Branch":[168],"Block),":[169],"captures":[172],"features":[173],"different":[175],"layers":[176],"types":[178],"image,":[181],"increasing":[182],"network\u2019s":[184],"diversity.":[185],"Experimental":[186],"results":[187],"demonstrate":[188],"that":[189],"YOLO-fall":[190,218],"improves":[191],"mAP":[192],"2.7%":[194],"compared":[195],"YOLOv7-tiny":[197],"while":[198],"reducing":[199],"3.5%":[203],"requirements":[206],"5.4%.":[208],"comparison":[210],"existing":[212],"algorithms":[214],"under":[215],"similar":[216],"conditions,":[217],"achieves":[219],"precise":[221],"lightweight":[223],"capabilities.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":12}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
