Zobrazeno 1 - 10
of 2 132
pro vyhledávání: '"A. Galar"'
Machine learning models can inherit biases from their training data, leading to discriminatory or inaccurate predictions. This is particularly concerning with the increasing use of large, unsupervised datasets for training foundational models. Tradit
Externí odkaz:
http://arxiv.org/abs/2406.17405
In the last few years, Artificial Intelligence systems have become increasingly widespread. Unfortunately, these systems can share many biases with human decision-making, including demographic biases. Often, these biases can be traced back to the dat
Externí odkaz:
http://arxiv.org/abs/2312.14626
Demographic biases in source datasets have been shown as one of the causes of unfairness and discrimination in the predictions of Machine Learning models. One of the most prominent types of demographic bias are statistical imbalances in the represent
Externí odkaz:
http://arxiv.org/abs/2303.15889
Publikováno v:
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Paris, France, 2023, pp. 3385-3395
Few-Shot Class Incremental Learning (FSCIL) is a challenging continual learning task, where limited training examples are available during several learning sessions. To succeed in this task, it is necessary to avoid over-fitting new classes caused by
Externí odkaz:
http://arxiv.org/abs/2303.04751
Facial Expression Recognition (FER) uses images of faces to identify the emotional state of users, allowing for a closer interaction between humans and autonomous systems. Unfortunately, as the images naturally integrate some demographic information,
Externí odkaz:
http://arxiv.org/abs/2210.05332
Publikováno v:
JPSCR: Journal of Pharmaceutical Science and Clinical Research, Vol 9, Iss 1, Pp 25-32 (2024)
Hipertensi menjadi masalah utama bagi masyarakat di Indonesia dengan prevalensi mencapai 32,2%. Berbagai jenis terapi pengobatan sudah banyak direkomendasikan salah satu yang direkomendasikan dari JNC VIII adalah penggunaan kombinasi antihipertensi k
Externí odkaz:
https://doaj.org/article/9e1512aa7e3e426ea39ec6e60707f914
Autor:
Sara Monzón, Sarai Varona, Anabel Negredo, Santiago Vidal-Freire, Juan Angel Patiño-Galindo, Natalia Ferressini-Gerpe, Angel Zaballos, Eva Orviz, Oskar Ayerdi, Ana Muñoz-Gómez, Alberto Delgado-Iribarren, Vicente Estrada, Cristina García, Francisca Molero, Patricia Sánchez-Mora, Montserrat Torres, Ana Vázquez, Juan-Carlos Galán, Ignacio Torres, Manuel Causse del Río, Laura Merino-Diaz, Marcos López, Alicia Galar, Laura Cardeñoso, Almudena Gutiérrez, Cristina Loras, Isabel Escribano, Marta E. Alvarez-Argüelles, Leticia del Río, María Simón, María Angeles Meléndez, Juan Camacho, Laura Herrero, Pilar Jiménez, María Luisa Navarro-Rico, Isabel Jado, Elaina Giannetti, Jens H. Kuhn, Mariano Sanchez-Lockhart, Nicholas Di Paola, Jeffrey R. Kugelman, Susana Guerra, Adolfo García-Sastre, Isabel Cuesta, Maripaz P. Sánchez-Seco, Gustavo Palacios
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-18 (2024)
Abstract The 2023 monkeypox (mpox) epidemic was caused by a subclade IIb descendant of a monkeypox virus (MPXV) lineage traced back to Nigeria in 1971. Person-to-person transmission appears higher than for clade I or subclade IIa MPXV, possibly cause
Externí odkaz:
https://doaj.org/article/b702225a6b8044b886dd81bd6742679e
Autor:
Zola, Francesco, Fernandez-Carrasco, Jose Alvaro, Bruse, Jan Lukas, Galar, Mikel, Geradts, Zeno
Biometric systems represent valid solutions in tasks like user authentication and verification, since they are able to analyze physical and behavioural features with high precision. However, especially when physical biometrics are used, as is the cas
Externí odkaz:
http://arxiv.org/abs/2208.00785
Publikováno v:
Proceedings of the Workshop on Artificial Intelligence Safety 2022 (AISafety 2022)
The increasing amount of applications of Artificial Intelligence (AI) has led researchers to study the social impact of these technologies and evaluate their fairness. Unfortunately, current fairness metrics are hard to apply in multi-class multi-dem
Externí odkaz:
http://arxiv.org/abs/2205.10049
Autor:
Sanchez-Aceves, Livier M., Gómez-Olivan, Leobardo Manuel, Pérez-Alvarez, Itzayana, Rosales-Pérez, Karina Elisa, Hernández-Navarro, María Dolores, Amado-Piña, Deysi, Natividad, Reyna, Galar-Martínez, Marcela, García-Medina, Sandra, Ramírez-García, J.J., Becerril, M.E., Dávila-Estrada, M.
Publikováno v:
In Science of the Total Environment 20 December 2024 957