Zobrazeno 1 - 10
of 517
pro vyhledávání: '"Ortega García P"'
Autor:
Daza, Roberto, Gomez, Luis F., Fierrez, Julian, Morales, Aythami, Tolosana, Ruben, Ortega-Garcia, Javier
This work introduces an innovative method for estimating attention levels (cognitive load) using an ensemble of facial analysis techniques applied to webcam videos. Our method is particularly useful, among others, in e-learning applications, so we tr
Externí odkaz:
http://arxiv.org/abs/2408.05523
Autor:
DeAndres-Tame, Ivan, Tolosana, Ruben, Melzi, Pietro, Vera-Rodriguez, Ruben, Kim, Minchul, Rathgeb, Christian, Liu, Xiaoming, Morales, Aythami, Fierrez, Julian, Ortega-Garcia, Javier, Zhong, Zhizhou, Huang, Yuge, Mi, Yuxi, Ding, Shouhong, Zhou, Shuigeng, He, Shuai, Fu, Lingzhi, Cong, Heng, Zhang, Rongyu, Xiao, Zhihong, Smirnov, Evgeny, Pimenov, Anton, Grigorev, Aleksei, Timoshenko, Denis, Asfaw, Kaleb Mesfin, Low, Cheng Yaw, Liu, Hao, Wang, Chuyi, Zuo, Qing, He, Zhixiang, Shahreza, Hatef Otroshi, George, Anjith, Unnervik, Alexander, Rahimi, Parsa, Marcel, Sébastien, Neto, Pedro C., Huber, Marco, Kolf, Jan Niklas, Damer, Naser, Boutros, Fadi, Cardoso, Jaime S., Sequeira, Ana F., Atzori, Andrea, Fenu, Gianni, Marras, Mirko, Štruc, Vitomir, Yu, Jiang, Li, Zhangjie, Li, Jichun, Zhao, Weisong, Lei, Zhen, Zhu, Xiangyu, Zhang, Xiao-Yu, Biesseck, Bernardo, Vidal, Pedro, Coelho, Luiz, Granada, Roger, Menotti, David
Publikováno v:
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRw 2024)
Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class variability, time and errors produced in manual labeling, and in some c
Externí odkaz:
http://arxiv.org/abs/2404.10378
Autor:
Ruiz-Garcia, Juan Carlos, Tolosana, Ruben, Vera-Rodriguez, Ruben, Morales, Aythami, Fierrez, Julian, Ortega-Garcia, Javier, Herreros-Rodriguez, Jaime
This article provides a comprehensive overview of recent research in the area of Child-Computer Interaction (CCI). The main contributions of the present article are two-fold. First, we present a novel longitudinal CCI database named ChildCIdbLong, wh
Externí odkaz:
http://arxiv.org/abs/2404.06919
Autor:
Ruiz-Garcia, Juan Carlos, Hojas, Carlos, Tolosana, Ruben, Vera-Rodriguez, Ruben, Morales, Aythami, Fierrez, Julian, Ortega-Garcia, Javier, Herreros-Rodriguez, Jaime
Publikováno v:
International Journal on Document Analysis and Recognition (IJDAR), 2024
This article proposes a novel Children-Computer Interaction (CCI) approach for the task of age group detection. This approach focuses on the automatic analysis of the time series generated from the interaction of the children with mobile devices. In
Externí odkaz:
http://arxiv.org/abs/2403.04574
Autor:
DeAlcala, Daniel, Morales, Aythami, Fierrez, Julian, Mancera, Gonzalo, Tolosana, Ruben, Ortega-Garcia, Javier
This article introduces the Membership Inference Test (MINT), a novel approach that aims to empirically assess if given data was used during the training of AI/ML models. Specifically, we propose two MINT architectures designed to learn the distinct
Externí odkaz:
http://arxiv.org/abs/2402.09225
Autor:
DeAndres-Tame, Ivan, Tolosana, Ruben, Vera-Rodriguez, Ruben, Morales, Aythami, Fierrez, Julian, Ortega-Garcia, Javier
Publikováno v:
IEEE Access, February 2024
Large Language Models (LLMs) such as GPT developed by OpenAI, have already shown astonishing results, introducing quick changes in our society. This has been intensified by the release of ChatGPT which allows anyone to interact in a simple conversati
Externí odkaz:
http://arxiv.org/abs/2401.13641
Autor:
Melzi, Pietro, Tolosana, Ruben, Vera-Rodriguez, Ruben, Kim, Minchul, Rathgeb, Christian, Liu, Xiaoming, DeAndres-Tame, Ivan, Morales, Aythami, Fierrez, Julian, Ortega-Garcia, Javier, Zhao, Weisong, Zhu, Xiangyu, Yan, Zheyu, Zhang, Xiao-Yu, Wu, Jinlin, Lei, Zhen, Tripathi, Suvidha, Kothari, Mahak, Zama, Md Haider, Deb, Debayan, Biesseck, Bernardo, Vidal, Pedro, Granada, Roger, Fickel, Guilherme, Führ, Gustavo, Menotti, David, Unnervik, Alexander, George, Anjith, Ecabert, Christophe, Shahreza, Hatef Otroshi, Rahimi, Parsa, Marcel, Sébastien, Sarridis, Ioannis, Koutlis, Christos, Baltsou, Georgia, Papadopoulos, Symeon, Diou, Christos, Di Domenico, Nicolò, Borghi, Guido, Pellegrini, Lorenzo, Mas-Candela, Enrique, Sánchez-Pérez, Ángela, Atzori, Andrea, Boutros, Fadi, Damer, Naser, Fenu, Gianni, Marras, Mirko
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail. This paper offers an overview of the Face R
Externí odkaz:
http://arxiv.org/abs/2311.10476
Autor:
Stragapede, Giuseppe, Vera-Rodriguez, Ruben, Tolosana, Ruben, Morales, Aythami, Damer, Naser, Fierrez, Julian, Ortega-Garcia, Javier
Analyzing keystroke dynamics (KD) for biometric verification has several advantages: it is among the most discriminative behavioral traits; keyboards are among the most common human-computer interfaces, being the primary means for users to enter text
Externí odkaz:
http://arxiv.org/abs/2311.06000
AI4Food-NutritionFW: A Novel Framework for the Automatic Synthesis and Analysis of Eating Behaviours
Autor:
Romero-Tapiador, Sergio, Tolosana, Ruben, Morales, Aythami, Espinosa-Salinas, Isabel, Freixer, Gala, Fierrez, Julian, Vera-Rodriguez, Ruben, Pau, Enrique Carrillo de Santa, de Molina, Ana Ramírez, Ortega-Garcia, Javier
Nowadays millions of images are shared on social media and web platforms. In particular, many of them are food images taken from a smartphone over time, providing information related to the individual's diet. On the other hand, eating behaviours are
Externí odkaz:
http://arxiv.org/abs/2309.06308
Autor:
Melzi, Pietro, Tolosana, Ruben, Vera-Rodriguez, Ruben, Delgado-Santos, Paula, Stragapede, Giuseppe, Fierrez, Julian, Ortega-Garcia, Javier
The application of mobile biometrics as a user-friendly authentication method has increased in the last years. Recent studies have proposed novel behavioral biometric recognition systems based on Transformers, which currently outperform the state of
Externí odkaz:
http://arxiv.org/abs/2307.01663