no code implementations • 20 Jun 2020 • Yongming Li, Lang Zhou, Lingyun Qin, Yuwei Zeng, Yuchuan Liu, Yan Lei, Pin Wang, Fan Li
To solve these two problems, based on the existing Parkinson speech feature data set, a deep double-side learning ensemble model is designed in this paper that can reconstruct speech features and samples deeply and simultaneously.
no code implementations • 17 Feb 2020 • Yongming Li, Yan Lei, Pin Wang, Yuchuan Liu
For the issue that class representation ability of abstract information is limited by small sample problem, a feature fusion strategy has been designed aiming to combining abstract information learned by HFESAE with original feature and obtain hybrid features for feature reduction.
no code implementations • 10 Feb 2020 • Xiaoheng Zhang, Yongming Li, Pin Wang, Xiaoheng Tan, Yuchuan Liu
In this paper, a novel PD classification algorithm based on sparse kernel transfer learning combined with a parallel optimization of samples and features is proposed.