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176 results on '"Yan, Jiayu"'

10. Feature-enhanced text-inception model for Chinese long text classification

Author

Guo Yang, Yan Jiayu, Xu Dongdong, Guo Zelin, and Huan Hai

Subjects
Medicine, Science
Abstract

Abstract To solve the problem regarding unbalanced distribution of multi-category Chinese long texts and improve the classification accuracy thereof, a data enhancement method was proposed. Combined with this method, a feature-enhanced text-inception model for Chinese long text classification was proposed. First, the model used a novel text-inception module to extract important shallow features of the text. Meanwhile, the bidirectional gated recurrent unit (Bi-GRU) and the capsule neural network were employed to form a deep feature extraction module to understand the semantic information in the text; K-MaxPooling was then used to reduce the dimension of its shallow and deep features and enhance the overall features. Finally, the Softmax function was used for classification. By comparing the classification effects with a variety of models, the results show that the model can significantly improve the accuracy of long Chinese text classification and has a strong ability to recognize long Chinese text features. The accuracy of the model is 93.97% when applied to an experimental dataset.

Published
2023
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33. Winter Wheat Yield Estimation with Color Index Fusion Texture Feature.

Author

Yang, Fuqin, Liu, Yang, Yan, Jiayu, Guo, Lixiao, Tan, Jianxin, Meng, Xiangfei, Xiao, Yibo, and Feng, Haikuan

Subjects
WINTER wheat, PARTIAL least squares regression, FARM management, AGRICULTURAL productivity, DRONE aircraft, DIGITAL images
Abstract

The rapid and accurate estimation of crop yield is of great importance for large-scale agricultural production and national food security. Using winter wheat as the research object, the effects of color indexes, texture feature and fusion index on yield estimation were investigated based on unmanned aerial vehicle (UAV) high-definition digital images, which can provide a reliable technical means for the high-precision yield estimation of winter wheat. In total, 22 visible color indexes were extracted using UAV high-resolution digital images, and a total of 24 texture features in red, green, and blue bands extracted by ENVI 5.3 were correlated with yield, while color indexes and texture features with high correlation and fusion indexes were selected to establish yield estimation models for flagging, flowering and filling stages using partial least squares regression (PLSR) and random forest (RF). The yield estimation model constructed with color indexes at the flagging and flowering stages, along with texture characteristics and fusion indexes at the filling stage, had the best accuracy, with R2 values of 0.70, 0.71 and 0.76 and RMSE values of 808.95 kg/hm2, 794.77 kg/hm2 and 728.85 kg/hm2, respectively. The accuracy of winter wheat yield estimation using PLSR at the flagging, flowering, and filling stages was better than that of RF winter wheat estimation, and the accuracy of winter wheat yield estimation using the fusion feature index was better than that of color and texture feature indexes; the distribution maps of yield results are in good agreement with those of the actual test fields. Thus, this study can provide a scientific reference for estimating winter wheat yield based on UAV digital images and provide a reference for agricultural farm management. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Graphdiyne‐Based Multiscale Catalysts for Ammonia Synthesis

Author

Zhao, Shuya, primary, Chen, Zhaoyang, additional, Liu, Huimin, additional, Qi, Lu, additional, Zheng, Zhiqiang, additional, Luan, Xiaoyu, additional, Gao, Yaqi, additional, Liu, Runyu, additional, Yan, Jiayu, additional, Bu, Fanle, additional, Xue, Yurui, additional, and Li, Yuliang, additional

Published
2023
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