{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T23:10:58Z","timestamp":1781046658360,"version":"3.54.1"},"reference-count":232,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3321800","type":"journal-article","created":{"date-parts":[[2023,10,4]],"date-time":"2023-10-04T17:43:21Z","timestamp":1696441401000},"page":"114680-114713","source":"Crossref","is-referenced-by-count":54,"title":["A Comprehensive Survey of Machine Learning Methods for Surveillance Videos Anomaly Detection"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3251-3719","authenticated-orcid":false,"given":"Nomica","family":"Choudhry","sequence":"first","affiliation":[{"name":"Faculty of Science, Engineering and Built Environment, Deakins University, Burwood VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8962-1222","authenticated-orcid":false,"given":"Jemal","family":"Abawajy","sequence":"additional","affiliation":[{"name":"Faculty of Science, Engineering and Built Environment, Deakins University, Burwood VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7848-0508","authenticated-orcid":false,"given":"Shamsul","family":"Huda","sequence":"additional","affiliation":[{"name":"Faculty of Science, Engineering and Built Environment, Deakins University, Burwood VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Imran","family":"Rao","sequence":"additional","affiliation":[{"name":"Blue Brackets Technologies, Islamabad, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2020.102920"},{"key":"ref207","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.12.093"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.3390\/s23021043"},{"key":"ref208","article-title":"Online robust principal component analysis with change point detection","author":"xiao","year":"2017","journal-title":"arXiv 1702 05698"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1007\/s41060-021-00265-1"},{"key":"ref205","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.152"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1002\/wics.1524"},{"key":"ref206","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-022-10841-6"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.107865"},{"key":"ref203","article-title":"Visual anomaly detection in video by variational autoencoder","author":"waseem","year":"2022","journal-title":"arXiv 2203 03872"},{"key":"ref52","year":"2023","journal-title":"Transfer Learning in 2023 What it is How it Works"},{"key":"ref204","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58577-8_20"},{"key":"ref55","author":"dutta","year":"2021","journal-title":"Predictive Maintainance Using LSTM - Application Based on IIoT"},{"key":"ref201","doi-asserted-by":"publisher","DOI":"10.1109\/TCC.2020.3001017"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2960654"},{"key":"ref202","author":"wang","year":"2018","journal-title":"Analyzing Optimistic Concurrency Control Anomalies and Solutions"},{"key":"ref209","doi-asserted-by":"publisher","DOI":"10.3390\/app9163337"},{"key":"ref210","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8876056"},{"key":"ref211","article-title":"An efficient one-class SVM for anomaly detection in the Internet of Things","author":"yang","year":"2021","journal-title":"arXiv 2104 11146"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.6036\/10304"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2948204"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/7450637"},{"key":"ref218","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03244-6"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3487075.3487191"},{"key":"ref219","article-title":"Efficient GAN-based anomaly detection","author":"zenati","year":"2018","journal-title":"arXiv 1802 06222"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3142247"},{"key":"ref216","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547868"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2017.8078496"},{"key":"ref217","doi-asserted-by":"publisher","DOI":"10.1109\/CVIDL51233.2020.00-93"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2020.103915"},{"key":"ref214","doi-asserted-by":"publisher","DOI":"10.1007\/s11036-021-01865-8"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2021.102600"},{"key":"ref215","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-92185-9_2"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052599"},{"key":"ref212","doi-asserted-by":"publisher","DOI":"10.3390\/su14106175"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.107969"},{"key":"ref213","doi-asserted-by":"publisher","DOI":"10.1109\/ICPHM.2019.8819434"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICSES55317.2022.9914213"},{"key":"ref8","year":"2021","journal-title":"Understanding LSTM Networks"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.70825"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.3390\/app11104590"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3290906"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2018.06.053"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-022-04393-9"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3991\/ijoe.v18i02.28019"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.3390\/s22176563"},{"key":"ref221","doi-asserted-by":"publisher","DOI":"10.3390\/s19051005"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging4020036"},{"key":"ref222","doi-asserted-by":"publisher","DOI":"10.3390\/math10142531"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-06551-0"},{"key":"ref220","doi-asserted-by":"publisher","DOI":"10.1186\/s13673-019-0203-8"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9746659"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.10.009"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.5120\/21264-3857"},{"key":"ref36","article-title":"Deep learning for anomaly detection: A survey","author":"chalapathy","year":"2019","journal-title":"arXiv 1901 03407"},{"key":"ref31","author":"brownlee","year":"2020","journal-title":"One-Class Classification Algorithms for Imbalanced Datasets"},{"key":"ref30","author":"brax","year":"2011","journal-title":"Anomaly detection in the surveillance domain"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3459992"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-022-09819-3"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58555-6_20"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref24","first-page":"79","article-title":"A survey of anomaly detection approaches in Internet of Things","volume":"10","author":"behniafar","year":"2018","journal-title":"ISeCure"},{"key":"ref23","first-page":"61","article-title":"Anomaly, novelty, one-class classification: A comprehensive introduction","volume":"3","author":"bartkowiak","year":"2011","journal-title":"Int J Comput Inf Syst Ind Manag Appl"},{"key":"ref26","author":"bhandari","year":"2021","journal-title":"Correlation vs Causation Difference Designs and Examples"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ISPA.2019.8868704"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/info13010002"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-169908"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2018.8451603"},{"key":"ref28","author":"biswal","year":"2023","journal-title":"Recurrent neural network tutorial"},{"key":"ref27","author":"biswal","year":"2023","journal-title":"Principal Component Analysis in Machine Learning Complete Guide"},{"key":"ref29","first-page":"4","article-title":"The BEHAVE video dataset: Ground truthed video for multi-person behavior classification","volume":"4","author":"blunsden","year":"2010","journal-title":"Ann BMVA"},{"key":"ref200","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00126"},{"key":"ref128","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.338"},{"key":"ref129","doi-asserted-by":"publisher","DOI":"10.3390\/s18124290"},{"key":"ref97","article-title":"Multiple instance learning for detecting anomalies over sequential real-world datasets","author":"kamranfar","year":"2022","journal-title":"arXiv 2210 01707"},{"key":"ref126","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2905606"},{"key":"ref96","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.119079","article-title":"Multiple instance-based video anomaly detection using deep temporal encoding&#x2013;decoding","volume":"214","author":"kamoona","year":"2023","journal-title":"Exp Syst Appl"},{"key":"ref127","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107256"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-14384-3"},{"key":"ref124","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/9583285"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2976134"},{"key":"ref125","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2015.01.001"},{"key":"ref93","author":"joshi","year":"2020","journal-title":"Exploring the Limits of Transfer Learning"},{"key":"ref133","doi-asserted-by":"publisher","DOI":"10.1142\/S1469026820500029"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123454"},{"key":"ref134","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-21735-7_7"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.3390\/s22041352"},{"key":"ref131","doi-asserted-by":"publisher","DOI":"10.1109\/ICE3IS56585.2022.10010080"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1109\/HONET50430.2020.9322814"},{"key":"ref132","author":"mahmood","year":"2021","journal-title":"Outlier Detection in Regression Analysis"},{"key":"ref130","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2021.102215"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.3390\/electronics12010029"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104456"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/BigData55660.2022.10020914"},{"key":"ref139","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2020.04.276"},{"key":"ref86","year":"2019","journal-title":"What Are the Pros and Cons of the PCA?"},{"key":"ref137","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2022.104488"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2929228"},{"key":"ref138","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.4135514"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.3390\/s23042358"},{"key":"ref135","doi-asserted-by":"publisher","DOI":"10.3390\/app11083523"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00803"},{"key":"ref136","first-page":"1379","article-title":"Abnormal event detection based on SVM in video surveillance","author":"miao","year":"2014","journal-title":"Proc IEEE Workshop Adv Res Technol Ind Appl (WARTIA)"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/6391750"},{"key":"ref144","doi-asserted-by":"publisher","DOI":"10.1109\/PIMRC48278.2020.9217309"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-020-05373-x"},{"key":"ref145","first-page":"1310","article-title":"On the difficulty of training recurrent neural networks","author":"pascanu","year":"2013","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.3390\/rs13245132"},{"key":"ref142","doi-asserted-by":"publisher","DOI":"10.1007\/s10915-022-02083-4"},{"key":"ref83","first-page":"282","article-title":"Robust anomaly detection using support vector machines","author":"hu","year":"2003","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref143","doi-asserted-by":"publisher","DOI":"10.23919\/APSIPAASC55919.2022.9980343"},{"key":"ref140","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1900654116"},{"key":"ref141","doi-asserted-by":"publisher","DOI":"10.1016\/j.micpro.2020.103303"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-47759-6"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.3390\/antibiotics10101267"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2018.10.002"},{"key":"ref229","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-019-10113-w"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.46254\/IN02.20220633"},{"key":"ref109","author":"lani","year":"2023","journal-title":"Assumptions of Logistic Regression"},{"key":"ref106","author":"kwet","year":"2023","journal-title":"The Rise of Smart Camera Networks and Why We Should Ban Them"},{"key":"ref227","first-page":"878","article-title":"Background subtraction algorithm based on Bayesian generative adversarial networks","volume":"44","author":"zheng","year":"2018","journal-title":"Acta Autom Sinica"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.3390\/s23063318"},{"key":"ref228","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/7384803"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.3390\/s19245429"},{"key":"ref104","author":"kumar","year":"2023","journal-title":"Linear Regression Explained With Real Life Example"},{"key":"ref225","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2019.121135"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3206367"},{"key":"ref105","author":"kumar","year":"2019","journal-title":"The Professionals Point Advantages and Disadvantages of Principal Component Analysis in Machine Learning"},{"key":"ref226","first-page":"1989","article-title":"Seeing isn&#x2019;t believing: Towards more robust adversarial attack against real world object detectors","author":"zhao","year":"2019","journal-title":"Proc ACM SIGSAC Conf Comput Commun Secur"},{"key":"ref77","author":"hanlon","year":"2017","journal-title":"How to solve the memory challenges of deep neural networks"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-9647-6_54"},{"key":"ref223","doi-asserted-by":"publisher","DOI":"10.3390\/s22124324"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.116743"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1198\/016214503000233"},{"key":"ref224","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-022-07096-7"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1080\/2150704X.2020.1779374"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109348"},{"key":"ref232","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2023.3238524"},{"key":"ref70","article-title":"A review on generative adversarial networks: Algorithms, theory, and applications","author":"gui","year":"2020","journal-title":"arXiv 2001 06937"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.01.097"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00713"},{"key":"ref230","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3086137"},{"key":"ref72","first-page":"315","article-title":"Foreground detection via robust low rank matrix decomposition including spatio-temporal constraint","volume":"7728","author":"guyon","year":"2012","journal-title":"Proc Int Conf Pattern Recognit"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03613-1"},{"key":"ref231","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-03243-2_845-1"},{"key":"ref68","author":"goel","year":"2023","journal-title":"Support vector machine Machine Learning"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2019.00127"},{"key":"ref117","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2019.8909882"},{"key":"ref69","article-title":"mil-benchmarks: Standardized evaluation of deep multiple-instance learning techniques","author":"grahn","year":"2021","journal-title":"arXiv 2105 01443"},{"key":"ref118","article-title":"Balancing reconstruction quality and regularisation in ELBO for VAEs","author":"lin","year":"0","journal-title":"arXiv 1909 03765"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11213529"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.08.011"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.12.001"},{"key":"ref116","first-page":"5124","article-title":"Noisy recurrent neural networks","author":"lim","year":"2021","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-811318-9.00027-2"},{"key":"ref113","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/TPAMI.2013.111","article-title":"Anomaly detection and localization in crowded scenes","volume":"36","author":"li","year":"2014","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09277-8"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.3390\/app12105051"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1145\/3432867.3432898"},{"key":"ref122","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3416298"},{"key":"ref123","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00684"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/APSIPAASC47483.2019.9023261"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1109\/DISCEX.2000.821506"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-800635-1.00011-2"},{"key":"ref121","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-017-5532-x"},{"key":"ref168","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2020.08.016"},{"key":"ref169","doi-asserted-by":"publisher","DOI":"10.1108\/DTA-01-2020-0019"},{"key":"ref170","first-page":"3244","article-title":"Autoencoder-based background reconstruction and foreground segmentation with background noise estimation","author":"sauvalle","year":"2022","journal-title":"Proc IEEE\/CVF Winter Conf Appl Comput Vis"},{"key":"ref177","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01192"},{"key":"ref178","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/2086613"},{"key":"ref175","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-03493-1_48"},{"key":"ref176","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065720500343"},{"key":"ref173","doi-asserted-by":"publisher","DOI":"10.1109\/CISP-BMEI.2016.7852682"},{"key":"ref174","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2020.3026724"},{"key":"ref171","doi-asserted-by":"publisher","DOI":"10.14778\/3538598.3538602"},{"key":"ref172","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-021-00514-x"},{"key":"ref179","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0212-5"},{"key":"ref180","first-page":"19598","article-title":"Autoencoders that don&#x2019;t overfit towards the identity","author":"steck","year":"2020","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref181","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988456"},{"key":"ref188","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-017-9545-7"},{"key":"ref189","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.01.029"},{"key":"ref186","doi-asserted-by":"publisher","DOI":"10.3390\/computers10070088"},{"key":"ref187","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.510"},{"key":"ref184","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00678"},{"key":"ref185","year":"2022","journal-title":"Linear vs Logistic Regression (Differences and Limitations)"},{"key":"ref182","article-title":"A survey on deep learning techniques for video anomaly detection","author":"suarez","year":"2020","journal-title":"arXiv 2009 14146"},{"key":"ref183","author":"sullivan","year":"2022","journal-title":"Linear Regression and Correlation"},{"key":"ref148","doi-asserted-by":"publisher","DOI":"10.1109\/Confluence51648.2021.9377055"},{"key":"ref149","author":"pedamkar","year":"2023","journal-title":"Recurrent Neural Network"},{"key":"ref146","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2007.02.001"},{"key":"ref147","doi-asserted-by":"publisher","DOI":"10.1504\/IJCVR.2020.108152"},{"key":"ref155","first-page":"935","article-title":"Abnormal crowd behavior detection using social force model","author":"raamin","year":"2009","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref156","article-title":"Interpretable additive recurrent neural networks for multivariate clinical time series","author":"rahman","year":"2021","journal-title":"arXiv 2109 07602"},{"key":"ref153","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58586-0_10"},{"key":"ref154","doi-asserted-by":"publisher","DOI":"10.1016\/j.rineng.2023.101026"},{"key":"ref151","year":"2023","journal-title":"The Ultimate Guide to Building Your Own LSTM Models"},{"key":"ref152","author":"prosise","year":"2023","journal-title":"PCA-Based Anomaly Detection"},{"key":"ref150","doi-asserted-by":"publisher","DOI":"10.3390\/math10091403"},{"key":"ref159","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093457"},{"key":"ref157","doi-asserted-by":"publisher","DOI":"10.3390\/s21134283"},{"key":"ref158","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-022-13954-1"},{"key":"ref166","author":"saini","year":"2022","journal-title":"Understanding Support Vector Machines (SVMs) in Depth"},{"key":"ref167","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.13337"},{"key":"ref164","doi-asserted-by":"publisher","DOI":"10.1016\/j.measen.2022.100503"},{"key":"ref165","doi-asserted-by":"publisher","DOI":"10.1145\/3416013.3426457"},{"key":"ref162","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.32.4.042106"},{"key":"ref163","author":"rout","year":"2023","journal-title":"Advantages and disadvantages of logistic regression"},{"key":"ref160","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2019.00206"},{"key":"ref161","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-021-01586-5"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.matpr.2022.01.171"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3390\/app12136665"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.comcom.2019.08.003","article-title":"Malware traffic classification using principal component analysis and artificial neural network for extreme surveillance","volume":"147","author":"arivudainambi","year":"2019","journal-title":"Comput Commun"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.5220\/0010312304550464"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/s22166080"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-021-03323-5"},{"key":"ref17","volume":"953","year":"2018","journal-title":"Detection of license plate using sliding window histogram of oriented gradient and support vector machines method"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.32604\/csse.2023.031605"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2018.2804766"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/rs14164110"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s12065-020-00424-6"},{"key":"ref1","first-page":"27","article-title":"Voice assistant for physically challenged individuals: Enhancing accessibility and independence","volume":"8","author":"aa","year":"2023","journal-title":"International Research Journal of Modernization in Engineering Technology and Science"},{"key":"ref191","doi-asserted-by":"publisher","DOI":"10.3390\/s21082811"},{"key":"ref192","doi-asserted-by":"publisher","DOI":"10.5121\/ijscai.2019.8201"},{"key":"ref190","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09406-3"},{"key":"ref199","doi-asserted-by":"crossref","first-page":"9","DOI":"10.3390\/jsan12010009","article-title":"Loitering detection using spatial&#x2013;temporal information for intelligent surveillance systems on a vision sensor","volume":"12","author":"harjoko","year":"2023","journal-title":"J Sensor Actuator Netw"},{"key":"ref197","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2021.108752"},{"key":"ref198","doi-asserted-by":"publisher","DOI":"10.3390\/s21093179"},{"key":"ref195","doi-asserted-by":"publisher","DOI":"10.1109\/ICONAT53423.2022.9726078"},{"key":"ref196","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104354"},{"key":"ref193","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05365-w"},{"key":"ref194","first-page":"397","article-title":"A review of supervised and unsupervised machine learning techniques for suspicious behavior recognition in intelligent surveillance system","volume":"14","author":"verma","year":"2019","journal-title":"Int J Inf Technol"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10271300.pdf?arnumber=10271300","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T20:03:45Z","timestamp":1699301025000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10271300\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":232,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3321800","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}