Zobrazeno 1 - 10
of 134
pro vyhledávání: '"Vera Rodriguez, Rubén"'
In 2021, the pioneering work on TypeNet showed that keystroke dynamics verification could scale to hundreds of thousands of users with minimal performance degradation. Recently, the KVC-onGoing competition has provided an open and robust experimental
Externí odkaz:
http://arxiv.org/abs/2405.01088
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:
Shahreza, Hatef Otroshi, Ecabert, Christophe, George, Anjith, Unnervik, Alexander, Marcel, Sébastien, Di Domenico, Nicolò, Borghi, Guido, Maltoni, Davide, Boutros, Fadi, Vogel, Julia, Damer, Naser, Sánchez-Pérez, Ángela, EnriqueMas-Candela, Calvo-Zaragoza, Jorge, Biesseck, Bernardo, Vidal, Pedro, Granada, Roger, Menotti, David, DeAndres-Tame, Ivan, La Cava, Simone Maurizio, Concas, Sara, Melzi, Pietro, Tolosana, Ruben, Vera-Rodriguez, Ruben, Perelli, Gianpaolo, Orrù, Giulia, Marcialis, Gian Luca, Fierrez, Julian
Large-scale face recognition datasets are collected by crawling the Internet and without individuals' consent, raising legal, ethical, and privacy concerns. With the recent advances in generative models, recently several works proposed generating syn
Externí odkaz:
http://arxiv.org/abs/2404.04580
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:
Melzi, Pietro, Rathgeb, Christian, Tolosana, Ruben, Vera-Rodriguez, Ruben, Morales, Aythami, Lawatsch, Dominik, Domin, Florian, Schaubert, Maxim
Publikováno v:
Proceedings of the International Joint Conference on Biometrics 2023, special session on "Synthetic Data in Biometrics"
This study investigates the possibility of mitigating the demographic biases that affect face recognition technologies through the use of synthetic data. Demographic biases have the potential to impact individuals from specific demographic groups, an
Externí odkaz:
http://arxiv.org/abs/2402.01472
Autor:
Stragapede, Giuseppe, Vera-Rodriguez, Ruben, Tolosana, Ruben, Morales, Aythami, DeAndres-Tame, Ivan, Damer, Naser, Fierrez, Julian, Garcia, Javier-Ortega, Gonzalez, Nahuel, Shadrikov, Andrei, Gordin, Dmitrii, Schmitt, Leon, Wimmer, Daniel, Grossmann, Christoph, Krieger, Joerdis, Heinz, Florian, Krestel, Ron, Mayer, Christoffer, Haberl, Simon, Gschrey, Helena, Yamagishi, Yosuke, Saha, Sanjay, Rasnayaka, Sanka, Wickramanayake, Sandareka, Sim, Terence, Gutfeter, Weronika, Baran, Adam, Krzyszton, Mateusz, Jaskola, Przemyslaw
This paper describes the results of the IEEE BigData 2023 Keystroke Verification Challenge (KVC), that considers the biometric verification performance of Keystroke Dynamics (KD), captured as tweet-long sequences of variable transcript text from over
Externí odkaz:
http://arxiv.org/abs/2401.16559
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