most citedBoost AI Power: Data Augmentation Strategies with unlabelled Data and Conformal Prediction, a Case in Alternative Herbal Medicine Discrimination with Electronic Nose

4 citations · 7 across the 4 of their papers we have counts for

collaborators

4 papers

q-bio.QM2021

Unsupervised cross-user adaptation in taste sensation recognition based on surface electromyography with conformal prediction and domain regularized component analysis

Hengyang Wang, Xianghao Zhan, Li Liu +5

Human taste sensation can be qualitatively described with surface electromyography. However, the pattern recognition models trained on one subject (the source domain) do not genera…

q-bio.QM2021

CPSC: Conformal prediction with shrunken centroids for efficient prediction reliability quantification and data augmentation, a case in alternative herbal medicine classification with electronic nose

Li Liu, Xianghao Zhan, Xikai Yang +6

In machine learning applications, the reliability of predictions is significant for assisted decision and risk control. As an effective framework to quantify the prediction reliabi…

q-bio.QM2021★ 3 cited

Classifying herbal medicine origins by temporal and spectral data mining of electronic nose

Li Liu, Xianghao Zhan, Ziheng Duan +6

The origins of herbal medicines are important for their treatment effect, which could be potentially distinguished by electronic nose system. As the odor fingerprint of herbal medi…

cs.LG2021★ 4 cited

Boost AI Power: Data Augmentation Strategies with unlabelled Data and Conformal Prediction, a Case in Alternative Herbal Medicine Discrimination with Electronic Nose

Li Liu, Xianghao Zhan, Rumeng Wu +7

Electronic nose has been proven to be effective in alternative herbal medicine classification, but due to the nature of supervised learning, previous research heavily relies on the…