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Jie Wang, Jie Yang, Jiafan He and Dongliang Peng
Semi-supervised learning has been proven to be effective in utilizing unlabeled samples to mitigate the problem of limited labeled data. Traditional semi-supervised learning methods generate pseudo-labels for unlabeled samples and train the classifier us...
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Hamed Raoofi, Asa Sabahnia, Daniel Barbeau and Ali Motamedi
Traditional methods of supervision in the construction industry are time-consuming and costly, requiring significant investments in skilled labor. However, with advancements in artificial intelligence, computer vision, and deep learning, these methods ca...
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Luis Zuloaga-Rotta, Rubén Borja-Rosales, Mirko Jerber Rodríguez Mallma, David Mauricio and Nelson Maculan
The forecasting of presidential election results (PERs) is a very complex problem due to the diversity of electoral factors and the uncertainty involved. The use of a hybrid approach composed of techniques such as machine learning (ML) and Simulation in ...
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Yanjun Li, Takaaki Yoshimura, Yuto Horima and Hiroyuki Sugimori
The detection of coronary artery stenosis is one of the most important indicators for the diagnosis of coronary artery disease. However, stenosis in branch vessels is often difficult to detect using computer-aided systems and even radiologists because of...
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Depeng Gao, Shuai Wang, Yuwei Yang, Haifei Zhang, Hao Chen, Xiangxiang Mei, Shuxi Chen and Jianlin Qiu
Servo motors play an important role in automation equipment and have been used in several manufacturing fields. However, the commonly used control methods need their parameters to be set manually, which is rather difficult, and this means that these meth...
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