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pro vyhledávání: '"Zhang, Xiaoheng"'
Stack autoencoder (SAE), as a representative deep network, has unique and excellent performance in feature learning, and has received extensive attention from researchers. However, existing deep SAEs focus on original samples without considering the
Externí odkaz:
http://arxiv.org/abs/2210.14956
The class imbalance problem is important and challenging. Ensemble approaches are widely used to tackle this problem because of their effectiveness. However, existing ensemble methods are always applied into original samples, while not considering th
Externí odkaz:
http://arxiv.org/abs/2206.13507
Autor:
Liu, Rui, Wan, Jianjun, Zhang, Peng, Wang, Yaqin, Zuo, Lei, Zhang, Xiaoheng, González-Jiménez, José María, Gervilla, Fernando
Publikováno v:
In Journal of Hazardous Materials 5 December 2024 480
Parkinson disease (PD)'s speech recognition is an effective way for its diagnosis, which has become a hot and difficult research area in recent years. As we know, there are large corpuses (segments) within one subject. However, too large segments wil
Externí odkaz:
http://arxiv.org/abs/2111.09014
Imbalanced learning is important and challenging since the problem of the classification of imbalanced datasets is prevalent in machine learning and data mining fields. Sampling approaches are proposed to address this issue, and cluster-based oversam
Externí odkaz:
http://arxiv.org/abs/2111.01371
Labeled speech data from patients with Parkinsons disease (PD) are scarce, and the statistical distributions of training and test data differ significantly in the existing datasets. To solve these problems, dimensional reduction and sample augmentati
Externí odkaz:
http://arxiv.org/abs/2002.03716
Publikováno v:
In Food Policy August 2023 119
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Akademický článek
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Autor:
Wu, Zhengyang, Xia, Guifeng, Zhang, Xiaoheng, Zhou, Fayuan, Ling, Jing, Ni, Xin, Li, Yongming
Publikováno v:
In Computers in Biology and Medicine December 2022 151 Part A