An Efficient Lightweight CNN Autoencoder for Skeleton-Based Video Anomaly Detection.
Saved in:
| Title: | An Efficient Lightweight CNN Autoencoder for Skeleton-Based Video Anomaly Detection. |
|---|---|
| Authors: | Labib, Mostafa Ibrahim1, mostafa.elkhalil@fa-hists.edu.eg, Mohamed, Fatma Harby1, fatma.mohamed@fa-hists.edu.eg |
| Source: | Engineering, Technology & Applied Science Research; Jun2026, Vol. 16 Issue 3, p36849-36855, 7p |
| Database: | Applied Science & Technology Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 195332579 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: An Efficient Lightweight CNN Autoencoder for Skeleton-Based Video Anomaly Detection. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Labib%2C+Mostafa+Ibrahim%22">Labib, Mostafa Ibrahim</searchLink><relatesTo>1</relatesTo>, <i>mostafa.elkhalil@fa-hists.edu.eg</i><br /><searchLink fieldCode="AU" term="%22Mohamed%2C+Fatma+Harby%22">Mohamed, Fatma Harby</searchLink><relatesTo>1</relatesTo>, <i>fatma.mohamed@fa-hists.edu.eg</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Engineering%2C+Technology+%26+Applied+Science+Research%22">Engineering, Technology & Applied Science Research</searchLink>; Jun2026, Vol. 16 Issue 3, p36849-36855, 7p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=195332579 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.48084/etasr.18897 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 7 StartPage: 36849 Titles: – TitleFull: An Efficient Lightweight CNN Autoencoder for Skeleton-Based Video Anomaly Detection. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Labib, Mostafa Ibrahim – PersonEntity: Name: NameFull: Mohamed, Fatma Harby IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 22414487 Numbering: – Type: volume Value: 16 – Type: issue Value: 3 Titles: – TitleFull: Engineering, Technology & Applied Science Research Type: main |
| ResultId | 1 |