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Xiaonan Si, Lei Wang, Wenchang Xu, Biao Wang and Wenbo Cheng
Gout is one of the most painful diseases in the world. Accurate classification of gout is crucial for diagnosis and treatment which can potentially save lives. However, the current methods for classifying gout periods have demonstrated poor performance a...
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Ashir Javeed, Muhammad Asim Saleem, Ana Luiza Dallora, Liaqat Ali, Johan Sanmartin Berglund and Peter Anderberg
Researchers have proposed several automated diagnostic systems based on machine learning and data mining techniques to predict heart failure. However, researchers have not paid close attention to predicting cardiac patient mortality. We developed a clini...
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Sapna Sadhwani, Baranidharan Manibalan, Raja Muthalagu and Pranav Pawar
The study in this paper characterizes lightweight IoT networks as being established by devices with few computer resources, such as reduced battery life, processing power, memory, and, more critically, minimal security and protection, which are easily vu...
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Mateo Cano-Solis, John R. Ballesteros and German Sanchez-Torres
Vegetation encroachment in power line corridors remains a major challenge for modern energy-dependent societies, as it can cause power outages and lead to significant financial losses. Unmanned Aerial Vehicles (UAVs) have emerged as a promising solution ...
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Xibin Wang, Qiong Zhou, Hui Li and Mei Chen
Imbalanced learning problems often occur in application scenarios and are additionally an important research direction in the field of machine learning. Traditional classifiers are substantially less effective for datasets with an imbalanced distribution...
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Tianhao Hou, Hongyan Xing, Xinyi Liang, Xin Su and Zenghui Wang
Marine sensors are highly vulnerable to illegal access network attacks. Moreover, the nation?s meteorological and hydrological information is at ever-increasing risk, which calls for a prompt and in depth analysis of the network behavior and traffic to d...
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Yongkun Deng, Chenghao Zhang, Nan Yang and Huaming Chen
Semi-supervised learning (SSL) is a popular research area in machine learning which utilizes both labeled and unlabeled data. As an important method for the generation of artificial hard labels for unlabeled data, the pseudo-labeling method is introduced...
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Subhashree Rout, Pradeep Kumar Mallick, Annapareddy V. N. Reddy and Sachin Kumar
Class imbalance is one of the significant challenges in classification problems. The uneven distribution of data samples in different classes may occur due to human error, improper/unguided collection of data samples, etc. The uneven distribution of clas...
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Xinyue Fan, Teng Liu, Hong Bao, Weiguo Pan, Tianjiao Liang and Han Li
In the field of computer vision, training a well-performing model on a dataset with a long-tail distribution is a challenging task. To address this challenge, image resampling is usually introduced as a simple and effective solution. However, when perfor...
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Viera Maslej-Kre?náková, Martin Sarnovský and Júlia Jacková
The work presented in this paper focuses on the use of data augmentation techniques applied in the domain of the detection of antisocial behavior. Data augmentation is a frequently used approach to overcome issues related to the lack of data or problems ...
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