Zobrazeno 1 - 10 of 35 pro vyhledávání: '"Ruisen Luo"'
1
Akademický článek
A convolutional recurrent neural network with attention framework for speech separation in monaural recordings
Autor: Chao Sun, Min Zhang, Ruijuan Wu, Junhong Lu, Guo Xian, Qin Yu, Xiaofeng Gong, Ruisen Luo
Publikováno v: Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Abstract Most speech separation studies in monaural channel use only a single type of network, and the separation effect is typically not satisfactory, posing difficulties for high quality speech separation. In this study, we propose a convolutional
Externí odkaz: https://doaj.org/article/d0e7c3a33d6b4689a893b61ff127b46f
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2
Akademický článek
Integrating Wildfires Propagation Prediction Into Early Warning of Electrical Transmission Line Outages
Autor: Songyi Dian, Peng Cheng, Qiang Ye, Jirong Wu, Ruisen Luo, Chen Wang, Dafeng Hui, Ning Zhou, Dong Zou, Qin Yu, Xiaofeng Gong
Publikováno v: IEEE Access, Vol 7, Pp 27586-27603 (2019)
Wildfires could pose a significant danger to electrical transmission lines and cause considerable losses to the power grids and residents nearby. Previous studies of preventing wildfire damages to electrical transmission lines mostly analyze wildfire
Externí odkaz: https://doaj.org/article/4553db7fa9294333afc9ba73c8292399
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3
Akademický článek
Feature Learning With a Divergence-Encouraging Autoencoder for Imbalanced Data Classification
Autor: Ruisen Luo, Qian Feng, Chen Wang, Xiaomei Yang, Haiyan Tu, Qin Yu, Shaomin Fei, Xiaofeng Gong
Publikováno v: IEEE Access, Vol 6, Pp 70197-70211 (2018)
Imbalanced data exists commonly in machine learning classification applications. Popular classification algorithms are based on the assumption that data in different classes are roughly equally distributed; however, extremely skewed data, with instan
Externí odkaz: https://doaj.org/article/49f21dc240494e678b7122793e57c4ca
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5
A deep learning based algorithm with multi-level feature extraction for automatic modulation recognition
Autor: Minghui Lin, Xiaofeng Gong, Ruihua Nie, Yu Qin, Ruisen Luo, Hang Zhang, Ruijuan Wu, Guo Xian
Publikováno v: Wireless Networks. 27:4665-4676
Automatic modulation recognition is a critical challenge in the field of cognitive radio. In the process of communication, radio signals are modulated in various modes and are interfered by the complex electromagnetic environment. To cope with these
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a5f9906268b826f01a3bef41f4e62815
https://doi.org/10.1007/s11276-021-02758-0
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8
Adaptive ensemble of classifiers with regularization for imbalanced data classification
Autor: Xiaofeng Gong, Chen Wang, Ruisen Luo, Dafeng Hui, Chengyuan Deng, Zhoulu Yu
Publikováno v: Information Fusion. 69:81-102
The dynamic ensemble selection of classifiers is an effective approach for processing label-imbalanced data classifications. However, such a technique is prone to overfitting, owing to the lack of regularization methods and the dependence on local ge
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0248b59e89fcc43d7ecd38e3d4b0e3cd
https://doi.org/10.1016/j.inffus.2020.10.017
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9
MMD-encouraging convolutional autoencoder: a novel classification algorithm for imbalanced data
Autor: Bian Tong, Li Yanming, Bin Li, Chen Wang, Xiaofeng Gong, Wang Zhiyuan, Ruijuan Wu, Ruisen Luo
Publikováno v: Applied Intelligence. 51:7384-7401
Imbalanced data classification problem is widely existed in commercial activities and social production. It refers to the scenarios with considerable gap of sample amount among classes, thus significantly deteriorating the performance of the traditio
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e6e1c4f31d02050ad99719cea1ceeb8e
https://doi.org/10.1007/s10489-021-02235-3
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