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http://148.72.244.84:8080/xmlui/handle/xmlui/2963Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Hiyam Hashem Saeed | - |
| dc.contributor.author | Abdulbasit Alazzawia | - |
| dc.date.accessioned | 2023-10-11T09:00:17Z | - |
| dc.date.available | 2023-10-11T09:00:17Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.citation | https://doi.org/10.24237/ASJ.01.02.620B | en_US |
| dc.identifier.issn | 2958-4612 | - |
| dc.identifier.issn | 2958-4612 | - |
| dc.identifier.uri | http://148.72.244.84:8080/xmlui/handle/xmlui/2963 | - |
| dc.description.abstract | SocialdistancehasbeencrucialinpreventingtherapidspreadoftheCOVID-19pandemicsincetheoutbreakbegan.Publicspacesneedtobesafeplaceswherean individual'ssocialdistancingisrespected. Most methodsofmeasuring socialdistancingconsistofthefollowingsteps:thesystem(i)monitorsandanalyzestheactualdistancesbetweenpeopleinreal-time;(ii)looksforviolationsofsocialdistancingamongthecrowds;and(iii)collectsinformationonandalertsthosewhoviolatetherules.Thispaperprovidesthefirstreviewofthesubstantialfocusofconvolutionalneuralnetworks(CNN)-basedtechniques. It has beenconductedtoidentifytheiradvantagesanddisadvantages.Thisarticleexaminesthemostfundamentalideasaboutsocialdistancing.Themethodsandknowledgeofthebasicalgorithmsusedbypreviousresearchersandstudies,aswellasthedatasetthatcanbeusedtoevaluatealgorithmsthatcantellwhenadistanceissafe.Keywords:Coronavirus2019,SocialDistancing,Method,COCO dataset. | en_US |
| dc.description.sponsorship | https://acadscij.uodiyala.edu.iq/ | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | univercit of diyala | en_US |
| dc.subject | Coronavirus2019,SocialDistancing,Method,COCO dataset. | en_US |
| dc.title | Analysis of the most Important Concepts Related to Social Distancing as A Result of COVID-19 Pandemic: A Review | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | مجلة ديالى للعلوم الاكاديمية / Academic Science Journal (Acad. Sci. J.) | |
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