A generalized three-tier hybrid model for classifying unseen (IoT devices) in smart home environments
Data drift caused due to network changes, new device additions, or model degradation alters the patterns learned by ML/DL models, resulting in poor classification performance. This creates the need for a generalized, drift-resilient model that can learn without retraining in dynamic environments. To...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
Nature Publishing Group
2025
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| Subjects: | |
| Online Access: | https://umpir.ump.edu.my/id/eprint/45922/1/A%20generalized%20three-tier%20hybrid%20model%20for%20classifying%20unseen%20%28IoT%20devices%29%20in%20smart%20home%20environments.pdf https://umpir.ump.edu.my/id/eprint/45922/ https://doi.org/10.1038/s41598-025-19303-0 |
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