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Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias and Antonio G. Ravelo-García
This study presents a novel approach for kernel selection based on Kullback?Leibler divergence in variational autoencoders using features generated by the convolutional encoder. The proposed methodology focuses on identifying the most relevant subset of ...
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Noah J. Bagazinski and Faez Ahmed
Ship design is a years-long process that requires balancing complex design trade-offs to create a ship that is efficient and effective. Finding new ways to improve the ship design process could lead to significant cost savings in the time and effort requ...
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Zhenhui Sun, Peihang Li, Dongchuan Wang, Qingyan Meng, Yunxiao Sun and Weifeng Zhai
The identification of urban functional zones (UFZs) is crucial for urban planning and optimizing industrial layout. Fusing remote sensing images and social perception data is an effective way to identify UFZs. Previous studies on UFZs recognition often i...
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Olga V. Okhlupina,Dmitry S. Murashko
Pág. 17 - 20
Among the common methods of combating spam, a special place is occupied by a probabilistic machine learning algorithm, which is based on the well-known Bayes theorem. The so-called "naive" Bayesian classifier establishes the class of the document by dete...
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Aikaterini P. Kyprioti, Alexandros A. Taflanidis, Norberto C. Nadal-Caraballo, Madison C. Yawn and Luke A. Aucoin
Surrogate models, also referenced as metamodels, have emerged as attractive data-driven, predictive models for storm surge estimation. They are calibrated based on an existing database of synthetic storm simulations and can provide fast-to-compute approx...
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Wenyi Zhou, Hongguang Fan, Jihong Zhu, Hui Wen and Ying Xie
This paper first studies the generalization ability of the convolutional layer as a feature mapper (CFM) for extracting image features and the classification ability of the multilayer perception (MLP) in a CNN. Then, a novel generalized hybrid probabilit...
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Haoxiang Xu, Tongyao Ren, Zhuangda Mo and Xiaohui Yang
Since the classification methods mentioned in previous studies are currently unable to meet the accuracy requirements for fault diagnosis in large-scale chemical industries, these methods are gradually being eliminated and rarely used. This research offe...
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Supanat Chamchuen, Apirat Siritaratiwat, Pradit Fuangfoo, Puripong Suthisopapan and Pirat Khunkitti
Power quality disturbance (PQD) is an influential situation that significantly declines the reliability of electrical distribution systems. Therefore, PQD classification is an important process for preventing system reliability degradation. This paper in...
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Hisham ElMoaqet, Jungyoon Kim, Dawn Tilbury, Satya Krishna Ramachandran, Mutaz Ryalat and Chao-Hsien Chu
Sleep apnea is a common sleep-related disorder that significantly affects the population. It is characterized by repeated breathing interruption during sleep. Such events can induce hypoxia, which is a risk factor for multiple cardiovascular and cerebrov...
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Andrea Apicella, Anna Corazza, Francesco Isgrò and Giuseppe Vettigli
The use of ontological knowledge to improve classification results is a promising line of research. The availability of a probabilistic ontology raises the possibility of combining the probabilities coming from the ontology with the ones produced by a mu...
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