{"id":"https://openalex.org/W7065713474","doi":null,"title":"Enhancing Security : Deep Learning Models for Anomaly Detection in Surveillance Videos","display_name":"Enhancing Security : Deep Learning Models for Anomaly Detection in Surveillance Videos","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W7065713474"},"language":"en","primary_location":{"id":"pmh:oai:www.theseus.fi:10024/861473","doi":null,"is_oa":true,"landing_page_url":"http://www.theseus.fi/handle/10024/861473","pdf_url":"http://www.theseus.fi/bitstream/10024/861473/2/Karunarathne_Lihini.pdf","source":{"id":"https://openalex.org/S4306400928","display_name":"Theseus (Ammattikorkeakoulujen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"fi=Ylempi AMK-opinn\u00e4ytety\u00f6|sv=H\u00f6gre YH-examensarbete|en=Master's thesis|"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://www.theseus.fi/bitstream/10024/861473/2/Karunarathne_Lihini.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Karunarathne, Lihini","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Karunarathne, Lihini","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9761000275611877,"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":0.9761000275611877,"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":0.009999999776482582,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.009700000286102295,"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/video-surveillance","display_name":"video surveillance","score":0.7770000100135803},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"anomaly detection","score":0.9049999713897705},{"id":"https://openalex.org/keywords/real-time-anomaly-detection","display_name":"real-time anomaly detection","score":0.6359999775886536},{"id":"https://openalex.org/keywords/3d-convolutional-neural-networks","display_name":"3D convolutional neural networks","score":0.9580000042915344},{"id":"https://openalex.org/keywords/resnet","display_name":"ResNet","score":0.8679999709129333},{"id":"https://openalex.org/keywords/temporal-context","display_name":"temporal context","score":0.9340000152587891},{"id":"https://openalex.org/keywords/ucf-crime-dataset","display_name":"UCF-Crime dataset","score":0.6850000023841858},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"multi-class classification","score":0.699999988079071},{"id":"https://openalex.org/keywords/security-computing","display_name":"security (computing)","score":0.6620000004768372}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8335999846458435},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7815999984741211},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7014999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.675599992275238},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5480999946594238},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5328999757766724},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5218999981880188},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4810999929904938},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3849000036716461},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.31290000677108765},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.27469998598098755},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.2565999925136566}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:www.theseus.fi:10024/861473","doi":null,"is_oa":true,"landing_page_url":"http://www.theseus.fi/handle/10024/861473","pdf_url":"http://www.theseus.fi/bitstream/10024/861473/2/Karunarathne_Lihini.pdf","source":{"id":"https://openalex.org/S4306400928","display_name":"Theseus (Ammattikorkeakoulujen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"fi=Ylempi AMK-opinn\u00e4ytety\u00f6|sv=H\u00f6gre YH-examensarbete|en=Master's thesis|"}],"best_oa_location":{"id":"pmh:oai:www.theseus.fi:10024/861473","doi":null,"is_oa":true,"landing_page_url":"http://www.theseus.fi/handle/10024/861473","pdf_url":"http://www.theseus.fi/bitstream/10024/861473/2/Karunarathne_Lihini.pdf","source":{"id":"https://openalex.org/S4306400928","display_name":"Theseus (Ammattikorkeakoulujen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"fi=Ylempi AMK-opinn\u00e4ytety\u00f6|sv=H\u00f6gre YH-examensarbete|en=Master's thesis|"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7065713474.pdf","grobid_xml":"https://content.openalex.org/works/W7065713474.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1806891645","https://openalex.org/W1810943226","https://openalex.org/W1992675968","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2163605009","https://openalex.org/W2271840356","https://openalex.org/W2964121744","https://openalex.org/W3035965352","https://openalex.org/W3096831136","https://openalex.org/W3129091525"],"related_works":["https://openalex.org/W7130849931","https://openalex.org/W4399530974","https://openalex.org/W4390052732","https://openalex.org/W4226074596","https://openalex.org/W4353050204","https://openalex.org/W4387951137","https://openalex.org/W3168749219","https://openalex.org/W3008687721","https://openalex.org/W7126164308","https://openalex.org/W4300773349"],"abstract_inverted_index":{"An":[0,18],"extensive":[1],"study":[2,160],"on":[3,148],"effective":[4,119,190],"methods":[5],"to":[6,59,98],"detect":[7],"anomalous":[8,125],"events":[9,126],"in":[10,15,33,102,120,127,175,194],"surveillance":[11,128,179],"videos":[12],"is":[13],"presented":[14],"this":[16,64],"research.":[17],"increasing":[19,49],"demand":[20],"for":[21,74,169],"reliable":[22],"and":[23,51,67,80,86,104,123,137,172,181,189],"efficient":[24],"anomaly":[25,39,62],"detection":[26,40],"systems":[27],"capable":[28],"of":[29,46,57,146,151,153,178,185,198],"identifying":[30,122],"various":[31],"anomalies":[32,106],"real":[34],"time":[35],"was":[36,92,118],"realized.":[37],"This":[38],"would":[41],"further":[42],"improve":[43],"the":[44,82,89,113,115,139,142,149,163,183,196],"lives":[45],"people":[47],"by":[48],"security":[50,171],"safety.":[52],"\\n":[53,110,158],"\\nTo":[54],"provide":[55],"examples":[56],"how":[58],"enable":[60],"real-time":[61],"detection,":[63],"work":[65],"explored":[66],"evaluated":[68],"three":[69],"different":[70],"deep":[71,166,199],"learning":[72,167,200],"architectures":[73],"multi-class":[75],"classification":[76],"with":[77,94,107],"residual":[78],"networks":[79],"developed":[81],"models:":[83],"2DCNN+RNN,":[84],"3DCNN,":[85],"(2+1)DCNN.":[87],"Then,":[88],"best-performing":[90],"model":[91],"optimized":[93,131,165],"event":[95,191],"excerpting":[96,192],"techniques":[97,193],"enhance":[99],"its":[100],"performance":[101,197],"detecting":[103],"classifying":[105,124],"temporal":[108],"context.":[109],"\\nBy":[111],"analyzing":[112],"results,":[114],"followed":[116],"method":[117],"accurately":[121],"video.":[129],"The":[130],"(2+1)DCNN":[132],"Model":[133],"exhibited":[134],"superior":[135],"performance.":[136],"achieved":[138],"Area":[140],"Under":[141],"Curve":[143],"(AUC)":[144],"value":[145],"81%":[147],"dataset":[150],"University":[152],"Central":[154],"Florida":[155],"(UCF)":[156],"Crime.":[157],"\\nThis":[159],"encourages":[161],"using":[162],"fine-tuned":[164],"models":[168],"enhanced":[170],"safety":[173],"measures":[174],"a":[176],"variety":[177],"environments":[180],"emphasizes":[182],"importance":[184],"high-quality":[186],"video":[187],"data":[188],"maximizing":[195],"models.":[201]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-10T00:00:00"}