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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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Sotirios Kontogiannis, Myrto Konstantinidou, Vasileios Tsioukas and Christos Pikridas
In viticulture, downy mildew is one of the most common diseases that, if not adequately treated, can diminish production yield. However, the uncontrolled use of pesticides to alleviate its occurrence can pose significant risks for farmers, consumers, and...
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Thomas Kopalidis, Vassilios Solachidis, Nicholas Vretos and Petros Daras
Recent technological developments have enabled computers to identify and categorize facial expressions to determine a person?s emotional state in an image or a video. This process, called ?Facial Expression Recognition (FER)?, has become one of the most ...
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Vijayendra D. Avina, Md Amiruzzaman, Stefanie Amiruzzaman, Linh B. Ngo and M. Ali Akber Dewan
In this paper, we propose a framework to convert American Sign Language (ASL) to English and English to ASL. Within this framework, we use a deep learning model along with the rolling average prediction that captures image frames from videos and classifi...
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HaeHwan Kim, Ho-Woong Lee, JinSung Lee, Okhwan Bae and Chung-Pyo Hong
Detecting and tracking objects of interest in videos is a technology that can be used in various applications. For example, identifying cell movements or mutations through videos obtained in real time can be useful information for decision making in the ...
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