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Shangcong Zhang, Yongfang Li, Xuefei Chen, Ruyi Zhou, Ziran Wu and Taha Zarhmouti
Fire pumps are the key components of water supply in a firefighting system. At present, there is a lack of fire water pump testing methods that intelligently detect faulty states. Existing testing approaches require manual operation, which leads to low e...
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Pedro Celard, Adrián Seara Vieira, José Manuel Sorribes-Fdez, Eva Lorenzo Iglesias and Lourdes Borrajo
In this study, we propose a novel Temporal Development Generative Adversarial Network (TD-GAN) for the generation and analysis of videos, with a particular focus on biological and medical applications. Inspired by Progressive Growing GAN (PG-GAN) and Tem...
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Renata Duraciová
The mutual identification of spatial objects is a fundamental issue when updating geographic data with other data sets. Representations of spatial objects in different sources may not have the same identifiers, which would unambiguously assign them to ea...
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Maryam Omar, Hafeez Ur Rehman, Omar Bin Samin, Moutaz Alazab, Gianfranco Politano and Alfredo Benso
Text-to-image synthesis is one of the most critical and challenging problems of generative modeling. It is of substantial importance in the area of automatic learning, especially for image creation, modification, analysis and optimization. A number of wo...
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Xinyu Wang and Yingjie Xiao
The rapid growth of ship traffic leads to traffic congestion, which causes maritime accidents. Accurate ship trajectory prediction can improve the efficiency of navigation and maritime traffic safety. Previous studies have focused on developing a ship tr...
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Luigi Gianpio Di Maggio, Eugenio Brusa and Cristiana Delprete
The Intelligent Fault Diagnosis of rotating machinery calls for a substantial amount of training data, posing challenges in acquiring such data for damaged industrial machinery. This paper presents a novel approach for generating synthetic data using a G...
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Reza Shahbazian and Irina Trubitsyna
Insights and analysis are only as good as the available data. Data cleaning is one of the most important steps to create quality data decision making. Machine learning (ML) helps deal with data quickly, and to create error-free or limited-error datasets....
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Guglielmo Daddi, Nicolaus Notaristefano, Fabrizio Stesina and Sabrina Corpino
This work considers global path planning enabled by generative adversarial networks (GANs) on a 2D grid world. These networks can learn statistical relationships between obstacles, goals, states, and paths. Given a previously unseen combination of obstac...
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Sagar Kora Venu and Sridhar Ravula
Medical image datasets are usually imbalanced due to the high costs of obtaining the data and time-consuming annotations. Training a deep neural network model on such datasets to accurately classify the medical condition does not yield the desired result...
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Ziyuan Gu, Meead Saberi, Majid Sarvi, Zhiyuan Liu
Pág. 901 - 921
Existing methods for calibrating link fundamental diagrams (FDs) often focus on a limited number of links and use grouping strategies that are largely dependent on roadway physical attributes alone. In this study, we propose a big data-driven two-stage c...
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