Cross-Domain Active Learning for Electronic Nose Drift Compensation
The problem of drift in the electronic nose (E-nose) is an important factor in the distortion of data. The existing active learning methods do not take into account the misalignment of the data feature distribution between different domains due to drift when selecting samples. For this, we proposed...
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| Autors principals: | , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI AG
2022-08-01
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| Col·lecció: | Micromachines |
| Matèries: | |
| Accés en línia: | https://www.mdpi.com/2072-666X/13/8/1260 |
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