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Lingli Zhang, Chengming Luo, Xiyun Ge, Yuxin Cao, Haobo Zhang and Gaifang Xin
The efficient coverage of underwater wireless sensor networks (UWSNs) has become increasingly important because of the scarcity of underwater node resources. Complex underwater environments, water flow forces, and undulating seabed reduce the coverage ef...
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Fei Xie, Dalong Zhang and Chengming Liu
Transformer models are now widely used for speech processing tasks due to their powerful sequence modeling capabilities. Previous work determined an efficient way to model speaker embeddings using the Transformer model by combining transformers with conv...
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Chengming Li, Zheng Wu, Lining Zhu, Li Liu and Chengcheng Zhang
The COVID-19 pandemic is a major problem facing humanity throughout the world. The rapid and accurate tracking of population flows may therefore be epidemiologically informative. This paper adopts a massive amount of daily population flow data (from Janu...
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Chengming Li, Zixian Fan, Zheng Wu, Zhaoxin Dai, Li Liu and Chengcheng Zhang
Catchment division constitutes the foundation for urban water flood forecasting but represents a technically challenging task. The accurate division of catchments is significant for precisely forecasting urban waterlogging. However, existing catchment di...
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Yan Chen, Chengming Zhang, Shouyi Wang, Jianping Li, Feng Li, Xiaoxia Yang, Yuanyuan Wang and Leikun Yin
Using satellite remote sensing has become a mainstream approach for extracting crop spatial distribution. Making edges finer is a challenge, while simultaneously extracting crop spatial distribution information from high-resolution remote sensing images ...
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Chengming Zhang, Shuai Gao, Xiaoxia Yang, Feng Li, Maorui Yue, Yingjuan Han, Hui Zhao, Ya?nan Zhang and Keqi Fan
When extracting winter wheat spatial distribution by using convolutional neural network (CNN) from Gaofen-2 (GF-2) remote sensing images, accurate identification of edge pixel is the key to improving the result accuracy. In this paper, an approach for ex...
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