{"id":"https://openalex.org/W4283820830","doi":"https://doi.org/10.1109/ncc55593.2022.9806755","title":"Deep Imbalanced Data Learning Approach for Video Anomaly Detection","display_name":"Deep Imbalanced Data Learning Approach for Video Anomaly Detection","publication_year":2022,"publication_date":"2022-05-24","ids":{"openalex":"https://openalex.org/W4283820830","doi":"https://doi.org/10.1109/ncc55593.2022.9806755"},"language":"en","primary_location":{"id":"doi:10.1109/ncc55593.2022.9806755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc55593.2022.9806755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 National Conference on Communications (NCC)","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/A5053444234","display_name":"Avinash Ratre","orcid":"https://orcid.org/0000-0001-9803-2665"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Avinash Ratre","raw_affiliation_strings":["IIT Roorkee,Department of ECE,Roorkee,India","Department of ECE, IIT Roorkee, Roorkee, India"],"affiliations":[{"raw_affiliation_string":"IIT Roorkee,Department of ECE,Roorkee,India","institution_ids":["https://openalex.org/I154851008"]},{"raw_affiliation_string":"Department of ECE, IIT Roorkee, Roorkee, India","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059884867","display_name":"Vinod Pankajakshan","orcid":"https://orcid.org/0000-0003-4525-5288"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vinod Pankajakshan","raw_affiliation_strings":["IIT Roorkee,Department of ECE,Roorkee,India","Department of ECE, IIT Roorkee, Roorkee, India"],"affiliations":[{"raw_affiliation_string":"IIT Roorkee,Department of ECE,Roorkee,India","institution_ids":["https://openalex.org/I154851008"]},{"raw_affiliation_string":"Department of ECE, IIT Roorkee, Roorkee, India","institution_ids":["https://openalex.org/I154851008"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053444234"],"corresponding_institution_ids":["https://openalex.org/I154851008"],"apc_list":null,"apc_paid":null,"fwci":0.5307,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70247399,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"391","last_page":"396"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11220","display_name":"Water Systems and Optimization","score":0.9782000184059143,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8244307041168213},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8093060255050659},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7978730201721191},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7700717449188232},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5402505397796631},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5394189953804016},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.46528878808021545},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45329731702804565},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4528329372406006},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.44461730122566223},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.40371769666671753}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8244307041168213},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8093060255050659},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7978730201721191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7700717449188232},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5402505397796631},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5394189953804016},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.46528878808021545},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45329731702804565},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4528329372406006},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.44461730122566223},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.40371769666671753},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ncc55593.2022.9806755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc55593.2022.9806755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 National Conference on Communications (NCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.75,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W728297","https://openalex.org/W1522301498","https://openalex.org/W1999318832","https://openalex.org/W2038083981","https://openalex.org/W2041497292","https://openalex.org/W2168091011","https://openalex.org/W2194775991","https://openalex.org/W2341058432","https://openalex.org/W2540481276","https://openalex.org/W2598548966","https://openalex.org/W2600520404","https://openalex.org/W2620395638","https://openalex.org/W2776460497","https://openalex.org/W2777288981","https://openalex.org/W2807796723","https://openalex.org/W2910421740","https://openalex.org/W2963111876","https://openalex.org/W2963596856","https://openalex.org/W2963795951","https://openalex.org/W2998540609","https://openalex.org/W3014352273","https://openalex.org/W3014666486","https://openalex.org/W3015832418","https://openalex.org/W3035082392","https://openalex.org/W3037420336","https://openalex.org/W3128635849","https://openalex.org/W3171765188","https://openalex.org/W6631190155","https://openalex.org/W6660695881","https://openalex.org/W6738532226","https://openalex.org/W6751611920","https://openalex.org/W6774179995"],"related_works":["https://openalex.org/W4396941953","https://openalex.org/W2093104230","https://openalex.org/W2987280934","https://openalex.org/W4390874210","https://openalex.org/W4384918963","https://openalex.org/W4365211920","https://openalex.org/W2128027845","https://openalex.org/W3014948380","https://openalex.org/W4386184937","https://openalex.org/W4394728283"],"abstract_inverted_index":{"Surveillance":[0],"video":[1,29,84,113],"data":[2,7,74,110,155],"often":[3,38],"exhibit":[4],"highly":[5],"imbal-anced":[6],"distribution,":[8],"i.e.,":[9,131],"majority":[10],"or":[11,18,47,57],"normal":[12],"class":[13,20],"instances":[14],"outnumber":[15],"the":[16,24,51,64,68,116,120],"minority":[17],"anomalous":[19],"instances,":[21],"which":[22],"are":[23],"point":[25],"of":[26,44,50,53,93,125],"concern":[27],"in":[28,66,78,160],"anomaly":[30],"detection":[31],"(AD).":[32],"The":[33,149],"existing":[34],"deep":[35,55,69,96,134,142,152],"learning":[36,59,70,75,97,111,121,156],"methods":[37,42,62],"adopt":[39],"various":[40],"ensemble":[41],"consisting":[43],"an":[45],"early":[46],"late":[48,91],"fusion":[49,92],"cascade":[52],"either":[54],"discriminative":[56,133],"generative":[58,141],"models.":[60],"These":[61],"lack":[63],"diversity":[65],"applying":[67],"algorithms":[71],"to":[72,164],"imbalanced":[73,82,109,154],"for":[76,112],"AD":[77],"real-world":[79],"unlabeled":[80],"and":[81,139],"surveillance":[83],"data.":[85],"In":[86],"this":[87],"paper,":[88],"decision":[89],"level":[90,118],"two":[94,126],"complementary":[95,127,151],"models":[98],"is":[99],"accomplished":[100],"using":[101],"a":[102,132,140],"loss":[103],"function":[104],"weighted":[105],"regression":[106,143],"model":[107],"towards":[108],"AD.":[114],"Under":[115],"algorithmic":[117],"actions,":[119],"model's":[122],"architecture":[123],"consists":[124],"parallel":[128],"discriminative-generative":[129],"channels,":[130],"residual":[135],"network":[136],"(DRN)":[137],"channel":[138],"long":[144],"short-term":[145],"memory":[146],"(LSTM)":[147],"channel.":[148],"proposed":[150],"LSTM-DRN-based":[153],"approach":[157],"improves":[158],"effectiveness":[159],"detecting":[161],"anomalies":[162],"compared":[163],"state-of-the-art":[165],"methods.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}