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Suryakant Tyagi and Sándor Szénási
Machine learning and speech emotion recognition are rapidly evolving fields, significantly impacting human-centered computing. Machine learning enables computers to learn from data and make predictions, while speech emotion recognition allows computers t...
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Naseer Muhammad Khan, Liqiang Ma, Muhammad Zaka Emad, Tariq Feroze, Qiangqiang Gao, Saad S. Alarifi, Li Sun, Sajjad Hussain and Hui Wang
The brittleness index is one of the most integral parameters used in assessing rock bursts and catastrophic rock failures resulting from deep underground mining activities. Accurately predicting this parameter is crucial for effectively monitoring rock b...
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José-Luis Molina, Santiago Zazo, Fernando Espejo, Carmen Patino-Alonso, Irene Blanco-Gutiérrez and Domingo Zarzo
Floods are probably the most hazardous global natural event as well as the main cause of human losses and economic damage. They are often hard to predict, but their consequences may be reduced by taking the right precautions. In this sense, hydraulic inf...
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Ruoyang Li, Shuping Xiong, Yinchao Che, Lei Shi, Xinming Ma and Lei Xi
Semantic segmentation algorithms leveraging deep convolutional neural networks often encounter challenges due to their extensive parameters, high computational complexity, and slow execution. To address these issues, we introduce a semantic segmentation ...
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Qi Zhu, Su-Mei Wang and Yi-Qing Ni
Maglev transportation is a highly promising form of transportation for the future, primarily due to its friction-free operation, exceptional comfort, and low risk of derailment. Unlike conventional transportation systems, maglev trains operate with no me...
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