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Diya Wang, Yonglin Zhang, Lixin Wu, Yupeng Tai, Haibin Wang, Jun Wang, Fabrice Meriaudeau and Fan Yang
In recent years, the study of deep learning techniques for underwater acoustic channel estimation has gained widespread attention. However, existing neural network channel estimation methods often overfit to training dataset noise levels, leading to dimi...
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Wanyuan Zhang, Weijia Yuan, Gongwu Sun, Tengjiao He, Junqi Qu and Chao Xu
The advancement of unmanned platforms is driving the miniaturization and cost reduction of the multi-beam echosounder (MBES). In the process of MBES array calibration, the mutual coupling significantly impacts the performance of parameter estimation. We ...
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Chenglin Yang, Dongliang Xu and Xiao Ma
Due to the increasing severity of network security issues, training corresponding detection models requires large datasets. In this work, we propose a novel method based on generative adversarial networks to synthesize network data traffic. We introduced...
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Andrea Maria Patelski, Urszula Dziekonska-Kubczak and Maciej Ditrych
Throughout history, the fermentation of fruit juices has served as a preservation method and has enhanced the retention of bioactive constituents crucial for human well-being. This study examined the possibility of orange and black currant juice fermenta...
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Qishun Mei and Xuhui Li
To address the limitations of existing methods of short-text entity disambiguation, specifically in terms of their insufficient feature extraction and reliance on massive training samples, we propose an entity disambiguation model called COLBERT, which f...
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