Sim-to-Real Domain Adaptation for Early Alzheimer's Detection from Handwriting Kinematics Using Hybrid Deep Learning.
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| Title: | Sim-to-Real Domain Adaptation for Early Alzheimer's Detection from Handwriting Kinematics Using Hybrid Deep Learning. |
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| Authors: | Bazarbekov I; Department of Computer Engineering, International IT University, Almaty 050040, Kazakhstan., Almisreb A; Department of Engineering, International University of Sarajevo, 71210 Sarajevo, Bosnia and Herzegovina., Ipalakova M; Department of Computer Engineering, International IT University, Almaty 050040, Kazakhstan., Bazarbekova M; Department of Recreational Geography and Tourism, Al Farabi Kazakh National University, Almaty 050040, Kazakhstan., Daineko Y; Department of Computer Engineering, International IT University, Almaty 050040, Kazakhstan.; Department of Electronics, Telecommunications and Space Technologies, Satbayev University, Almaty 050000, Kazakhstan. |
| Source: | Sensors (Basel, Switzerland) [Sensors (Basel)] 2026 Jan 02; Vol. 26 (1). Date of Electronic Publication: 2026 Jan 02. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1424-8220 |
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| DOI: | 10.3390/s26010298 |
