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Your search keyword '"Huang, Yingying"' showing total 1,739 results
Start Over Author "Huang, Yingying" Publication Type Periodicals
1,739 results on '"Huang, Yingying"'

5. A Knowledge-Driven Cross-view Contrastive Learning for EEG Representation

Author

Weng, Weining, Gu, Yang, Zhang, Qihui, Huang, Yingying, Miao, Chunyan, and Chen, Yiqiang

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, 68T30 Knowledge representation, I.2.4, I.5.2, J.3.1
Abstract

Due to the abundant neurophysiological information in the electroencephalogram (EEG) signal, EEG signals integrated with deep learning methods have gained substantial traction across numerous real-world tasks. However, the development of supervised learning methods based on EEG signals has been hindered by the high cost and significant label discrepancies to manually label large-scale EEG datasets. Self-supervised frameworks are adopted in vision and language fields to solve this issue, but the lack of EEG-specific theoretical foundations hampers their applicability across various tasks. To solve these challenges, this paper proposes a knowledge-driven cross-view contrastive learning framework (KDC2), which integrates neurological theory to extract effective representations from EEG with limited labels. The KDC2 method creates scalp and neural views of EEG signals, simulating the internal and external representation of brain activity. Sequentially, inter-view and cross-view contrastive learning pipelines in combination with various augmentation methods are applied to capture neural features from different views. By modeling prior neural knowledge based on homologous neural information consistency theory, the proposed method extracts invariant and complementary neural knowledge to generate combined representations. Experimental results on different downstream tasks demonstrate that our method outperforms state-of-the-art methods, highlighting the superior generalization of neural knowledge-supported EEG representations across various brain tasks., Comment: 14pages,7 figures

Published
2023

17. Status of aquatic organisms resources and their environments in Yangtze River system (2017–2021)

Author

Yang, Haile, Shen, Li, He, Yongfeng, Tian, Huiwu, Gao, Lei, Wu, Jinming, Mei, Zhigang, Wei, Nian, Wang, Lin, Zhu, Tingbing, Hu, Feifei, Gong, Jinling, Du, Hongchun, Duan, Xinbin, Deng, Huatang, Wang, Daoqun, Zhu, Fengyue, Li, Yunfeng, Wu, Fan, Ru, Huijun, Zhang, Yan, Li, Junyi, Yang, Junlin, Zhou, Yuntao, Fang, Dongdong, Wang, Yinping, Lin, Danqing, Yang, Yanping, Li, Peijie, Liu, Silei, Yang, Jian, Zhuang, Ping, Wang, Sikai, Zhang, Tao, Yang, Gang, Yang, Wenbo, Yuan, Lilai, Cao, Kun, Xu, Shuo, Liu, Huiyuan, Liang, Zhiqiang, Wang, Chongrui, Li, Hong, Yuan, Xiping, Yang, Xin, Fu, Yilong, Zhang, Yanping, Zhang, Haixin, Tao, Zhiying, Wang, Sheng, Gao, Xiaoping, Jin, Binsong, Li, Kemao, Wang, Guojie, Jian, Shenglong, Li, Yingqin, Xue, Chenjiang, Lei, Chunyun, Xue, Shaowei, Sun, Yi, Zhu, Bin, Shao, Ke, Hu, Xingkun, Xiong, Meihua, Du, Jun, He, Bin, Yan, Tao, Huang, Yingying, Zou, Yuanchao, Xie, Biwen, Wang, Yongming, Li, Bin, Liu, Fei, Zhang, Yaoyao, Fan, Fei, Wang, Zhijian, Huang, Jing, Gu, Haoran, Ge, Hailong, Dan, Yan, Li, Yan, Wang, Shuqiao, Zhang, Chuang, Zhou, Lu, Wang, Xue, Zeng, Sheng, Xiang, Yan, He, Xugang, Qin, Jianhui, Xia, Chengxing, Hou, Jie, Shi, Yifu, Gao, Lifang, Zhu, Zhiqiang, Shen, Hongbao, Du, Yun, Duan, Xuejun, Xiong, Jiawu, Yang, Deguo, Liu, Shaoping, Ni, Zhaohui, Zhang, Hui, Liu, Kai, Zhao, Feng, Li, Yingren, Wang, Jianwei, and Wei, Qiwei

Published
2024
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38. Information-based teaching model of college modeling foundation course based on ADDIE model

Author

Huang Yingying

Subjects
addie model, bp neural network, basic modeling course, sketching design, informatization, 62g08, Mathematics, QA1-939
Abstract

Education informatization is an inevitable change in using information technology for education development in the education field in the information age. This study firstly takes Guilin college teachers as the research object, based on the ADDIE model and optimized BP neural network algorithm, and tries to understand the current situation of using informationized teaching resources of basic modeling course college teachers. Secondly, by analyzing the data collected from students’ evaluation of the ability to use informationized teaching resources of drawing design teachers in the basic modeling course, we found that there are still some problems in the informationized teaching of basic modeling courses in colleges and universities, and we explore these problems in depth. The analysis shows that 80.9% of teachers will use teaching equipment when teaching and 92.72% of teachers will use teaching tools. The students rated the teachers’ ability to use informatization teaching resources highly, and about 50% thought that teachers could use them. College teachers need to establish an awareness of lifelong learning and take the initiative to adapt to the needs of information-based teaching.

Published
2024
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39. Analysis of the impact of ADDIE education model based on logistic regression model on teaching contemporary cultural and creative product design

Author

Huang Yingying

Subjects
logistic regression algorithm, sparse prior factors, addie model, likelihood function, cultural and creative design, 65d17, Mathematics, QA1-939
Abstract

Exploring the influence of the ADDIE education model on teaching cultural and creative product design to promote the improvement of the quality of teaching cultural and creative product design. Starting from the ADDIE education model, this paper analyzes the five components of the model and the specific functions of each component. The logistic regression algorithm that constitutes the analysis module of the ADDIE education model is introduced, and a sparse prior factor is introduced to optimize the logistic regression algorithm; then, a sparse logistic regression algorithm is constructed to solve the likelihood function of the weight vector. Finally, the ADDIE education model is used to analyze the indicators of cultural and creative product design teaching in two aspects: the teaching objectives and teaching principles of cultural and creative product design. From the teaching objectives, the influence of cognitive, skill, and emotional objectives accounted for 47.11%, 44.41% and 51.26%, respectively. From the teaching principles, the percentages of uniqueness, practicality, and attractiveness are 51.5%, 43.7%, and 40.3%, respectively. Based on the ADDIE education model can affect the emotional goals and uniqueness in the teaching of cultural and creative product design, and it is necessary to focus on the emotional teaching of product design as well as diversified and differentiated teaching in design teaching in order to enhance better the learners’ interest degree in cultural and creative product design.

Published
2024
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40. Aggregation Characteristics and Social Influencing Factors of COVID-19 in Shijiazhuang

Author

Wei, Xufan, Shang, Zhihai, Jiang, Baolin, Huang, Yingying, Appolloni, Andrea, Series Editor, Caracciolo, Francesco, Series Editor, Ding, Zhuoqi, Series Editor, Gogas, Periklis, Series Editor, Huang, Gordon, Series Editor, Nartea, Gilbert, Series Editor, Ngo, Thanh, Series Editor, Striełkowski, Wadim, Series Editor, Qiao, Sen, editor, Cao, Hongbin, editor, Liu, Aiwen, editor, Chen, Xueliang, editor, and Li, Tiefei, editor

Published
2023
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