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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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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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Mathias Højgaard Jensen and Stefan Sommer
Computing sample means on Riemannian manifolds is typically computationally costly, as exemplified by computation of the Fréchet mean, which often requires finding minimizing geodesics to each data point for each step of an iterative optimization scheme....
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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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