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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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Jin-Woo Kong, Byoung-Doo Oh, Chulho Kim and Yu-Seop Kim
Intracerebral hemorrhage (ICH) is a severe cerebrovascular disorder that poses a life-threatening risk, necessitating swift diagnosis and treatment. While CT scans are the most effective diagnostic tool for detecting cerebral hemorrhage, their interpreta...
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Hui-Jun Kim, Jung-Soon Kim and Sung-Hee Kim
The existing question-and-answer screening test has a limitation in that test accuracy varies due to a high learning effect and based on the inspector?s competency, which can have consequences for rapid-onset cognitive-related diseases. To solve this pro...
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Michal Brzus, Kevin Knoernschild, Jessica C. Sieren and Hans J. Johnson
Translation of basic animal research to find effective methods of diagnosing and treating human neurological disorders requires parallel analysis infrastructures. Small animals such as mice provide exploratory animal disease models. However, many interve...
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Ahram Song
Deep learning techniques have recently shown remarkable efficacy in the semantic segmentation of natural and remote sensing (RS) images. However, these techniques heavily rely on the size of the training data, and obtaining large RS imagery datasets is d...
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