29   Artículos

 
en línea
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... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
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... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
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... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
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 ... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
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... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
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... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
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... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
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... ver más
Revista: Information    Formato: Electrónico

 
en línea
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... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Branislav Dimitrijevic, Sina Darban Khales, Roksana Asadi and Joyoung Lee    
Highway crashes, along with the property damage, personal injuries, and fatalities that they cause, continue to present one of the most significant and critical transportation problems. At the same time, provision of safe travel is one of the main goals ... ver más
Revista: Applied Sciences    Formato: Electrónico

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