{"id":"https://openalex.org/W4408861113","doi":"https://doi.org/10.1109/icca62237.2024.10927782","title":"Developing Facial Recognition-Based Reconnaissance to Enhance Stadium Security and Detect Banned Fans at Soccer Stadiums","display_name":"Developing Facial Recognition-Based Reconnaissance to Enhance Stadium Security and Detect Banned Fans at Soccer Stadiums","publication_year":2024,"publication_date":"2024-12-17","ids":{"openalex":"https://openalex.org/W4408861113","doi":"https://doi.org/10.1109/icca62237.2024.10927782"},"language":"en","primary_location":{"id":"doi:10.1109/icca62237.2024.10927782","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icca62237.2024.10927782","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Computer and Applications (ICCA)","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/A5116805965","display_name":"Timothy Agboada","orcid":null},"institutions":[{"id":"https://openalex.org/I103087548","display_name":"Norfolk State University","ror":"https://ror.org/030pydv62","country_code":"US","type":"education","lineage":["https://openalex.org/I103087548"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timothy Agboada","raw_affiliation_strings":["Norfolk State University,Department of Computer Science,Norfolk,VA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norfolk State University,Department of Computer Science,Norfolk,VA,USA","institution_ids":["https://openalex.org/I103087548"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102808520","display_name":"Isaac O. Osunmakinde","orcid":"https://orcid.org/0000-0002-3351-0088"},"institutions":[{"id":"https://openalex.org/I103087548","display_name":"Norfolk State University","ror":"https://ror.org/030pydv62","country_code":"US","type":"education","lineage":["https://openalex.org/I103087548"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Isaac Osunmakinde","raw_affiliation_strings":["Norfolk State University,Department of Computer Science,Norfolk,VA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norfolk State University,Department of Computer Science,Norfolk,VA,USA","institution_ids":["https://openalex.org/I103087548"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057465112","display_name":"Claude Turner","orcid":"https://orcid.org/0000-0001-9723-7036"},"institutions":[{"id":"https://openalex.org/I103087548","display_name":"Norfolk State University","ror":"https://ror.org/030pydv62","country_code":"US","type":"education","lineage":["https://openalex.org/I103087548"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Claude Turner","raw_affiliation_strings":["Norfolk State University,Department of Computer Science,Norfolk,VA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norfolk State University,Department of Computer Science,Norfolk,VA,USA","institution_ids":["https://openalex.org/I103087548"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046102769","display_name":"Kingsley C. Nwosu","orcid":"https://orcid.org/0000-0001-7235-2708"},"institutions":[{"id":"https://openalex.org/I103087548","display_name":"Norfolk State University","ror":"https://ror.org/030pydv62","country_code":"US","type":"education","lineage":["https://openalex.org/I103087548"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kingsley Nwosu","raw_affiliation_strings":["Norfolk State University,Department of Computer Science,Norfolk,VA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norfolk State University,Department of Computer Science,Norfolk,VA,USA","institution_ids":["https://openalex.org/I103087548"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I103087548"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24497621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9771999716758728,"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":0.9771999716758728,"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/T12406","display_name":"IoT and GPS-based Vehicle Safety Systems","score":0.9258000254631042,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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":0.9212999939918518,"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/stadium","display_name":"Stadium","score":0.9644813537597656},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47927090525627136},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4079740643501282},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3314115107059479},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09206169843673706}],"concepts":[{"id":"https://openalex.org/C2778539849","wikidata":"https://www.wikidata.org/wiki/Q7596467","display_name":"Stadium","level":2,"score":0.9644813537597656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47927090525627136},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4079740643501282},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3314115107059479},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09206169843673706},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icca62237.2024.10927782","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icca62237.2024.10927782","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Computer and Applications (ICCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2106398051","https://openalex.org/W2341528187","https://openalex.org/W2480418144","https://openalex.org/W2739722733","https://openalex.org/W2792492450","https://openalex.org/W2943428689","https://openalex.org/W2981408674","https://openalex.org/W2981555962","https://openalex.org/W2982232682","https://openalex.org/W2999309192","https://openalex.org/W3014348756","https://openalex.org/W3014890713","https://openalex.org/W3168997536","https://openalex.org/W3199653926","https://openalex.org/W4248605585","https://openalex.org/W4312364466","https://openalex.org/W4361852634","https://openalex.org/W6674330103","https://openalex.org/W6762718338"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4295007445","https://openalex.org/W2493948198","https://openalex.org/W652905856","https://openalex.org/W2289096763","https://openalex.org/W2011117680","https://openalex.org/W386305294","https://openalex.org/W2486266501"],"abstract_inverted_index":{"Soccer":[0],"or":[1],"football":[2],"outside":[3],"of":[4,29,105,168,174],"North":[5],"America":[6],"remains":[7],"a":[8,61,102,122,149],"major":[9],"global":[10],"industry":[11],"but":[12],"faces":[13,109,114],"ongoing":[14],"issues":[15],"with":[16,38],"hooliganism":[17],"and":[18,51,84,92,110,130,139,151,185],"stadium":[19,34,73,160],"violence,":[20],"which":[21,99,134],"often":[22],"involves":[23],"banned":[24,68],"fans.":[25],"Despite":[26],"the":[27,96,166,172],"severity":[28],"these":[30],"challenges,":[31],"research":[32,59,147],"on":[33],"security":[35],"is":[36],"limited":[37],"most":[39],"studies":[40],"utilizing":[41],"Convolutional":[42],"Neural":[43],"Networks":[44],"(CNNs)":[45],"for":[46,80,107,112,171],"tasks":[47],"such":[48],"as":[49,115],"attendance":[50],"emotion":[52],"detection":[53,83,103],"rather":[54],"than":[55],"crowd":[56],"security.":[57,74,161],"This":[58,75,146],"introduces":[60],"facial":[62,82,153,175],"recognition":[63,176],"system":[64,76],"aimed":[65],"at":[66],"identifying":[67],"soccer":[69,159],"fans":[70],"to":[71,101,132,158,183],"enhance":[72],"leverages":[77],"Siamese":[78],"CNNs":[79],"accurate":[81],"matching":[85],"using":[86],"publicly":[87],"available":[88],"data.":[89],"Data":[90],"preprocessing":[91],"augmentation":[93],"strategies":[94],"improved":[95],"model":[97],"resilience,":[98],"leads":[100],"accuracy":[104,141],"94.45%":[106],"unoccluded":[108],"89.85%":[111],"occluded":[113],"it":[116],"surpasses":[117],"traditional":[118],"CNN":[119],"models":[120],"by":[121,181],"significant":[123],"margin.":[124],"Additional":[125],"testing":[126],"addressed":[127],"demographic":[128],"bias":[129],"robustness":[131],"occlusions,":[133],"results":[135],"in":[136,178],"enhanced":[137],"fairness":[138],"balanced":[140],"across":[142],"different":[143],"racial":[144],"groups.":[145],"offers":[148],"reliable":[150],"unbiased":[152],"recognition-based":[154],"reconnaissance":[155],"solution":[156],"tailored":[157],"The":[162],"findings":[163],"can":[164],"guide":[165],"development":[167],"best":[169],"practices":[170],"deployment":[173],"technologies":[177],"sports":[179],"venues":[180],"contributing":[182],"safer":[184],"more":[186],"secure":[187],"environments.":[188]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
