Applying knowledge distillation to the UCI gas sensor drift dataset yields higher accuracy and F1 than the DRCA baseline in a majority of cross-batch tasks, though the improvement is not consistently significant.
Application of a low-cost electronic nose for differentiation between pathogenic oomycetes pythium intermedium and phytophthora plurivora,
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Sensor Drift Compensation in Electronic-Nose-Based Gas Recognition Using Knowledge Distillation
Applying knowledge distillation to the UCI gas sensor drift dataset yields higher accuracy and F1 than the DRCA baseline in a majority of cross-batch tasks, though the improvement is not consistently significant.