Energy-Efficient TinyML Approach for Wearable Fall Detection on Edge Devices Using Spatial-Temporal Deep Learning.
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| Title: | Energy-Efficient TinyML Approach for Wearable Fall Detection on Edge Devices Using Spatial-Temporal Deep Learning. |
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| Authors: | Duan, Luong-Cong1, duanlc@ptit.edu.vn, Minh, Nguyen-Ngoc1, Dung, Truong-Cao1, Linh, Tran-T.-Thuc1 |
| Source: | International Journal of Technology; 2026, Vol. 17 Issue 3, p919-935, 17p |
| Database: | Applied Science & Technology Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 194237674 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=194237674 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.14716/ijtech.v17i3.8445 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 919 Titles: – TitleFull: Energy-Efficient TinyML Approach for Wearable Fall Detection on Edge Devices Using Spatial-Temporal Deep Learning. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Duan, Luong-Cong – PersonEntity: Name: NameFull: Minh, Nguyen-Ngoc – PersonEntity: Name: NameFull: Dung, Truong-Cao – PersonEntity: Name: NameFull: Linh, Tran-T.-Thuc IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20869614 Numbering: – Type: volume Value: 17 – Type: issue Value: 3 Titles: – TitleFull: International Journal of Technology Type: main |
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