Listar por tema "explainable artificial intelligence"
Mostrando ítems 1-6 de 6
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Analysis of Gender Differences in Facial Expression Recognition Based on Deep Learning Using Explainable Artificial Intelligence
(International Journal of Interactive Multimedia and Artificial Intelligence, 2024)Potential uses of automated Facial Expression Recognition (FER) cover a wide range of applications such as customer behavior analysis, healthcare applications or providing personalized services. Data for machine learning ... -
Arquitectura técnica distribuida y gobernanza del dato en entornos sanitarios conforme al marco regulatorio Europeo emergente
(Dyna, 2025)The new digital transformation of the European healthcare sector is structured around the emerging concept of Healthcare 5.0. This evolution is driven by new enabling technologies, including artificial intelligence, advanced ... -
OBOE: an Explainable Text Classification Framework
(International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2024)Explainable Artificial Intelligence (XAI) has recently gained visibility as one of the main topics of Artificial Intelligence research due to, among others, the need to provide a meaningful justification of the reasons ... -
STEG-XAI: explainable steganalysis in images using neural networks
(Multimedia Tools and Applications, 2024)Multimedia content’s development and technological evolution have enhanced and even facilitated the application of steganography as a means to introduce hidden messages for cybercrime-related purposes. Artificial intelligence ... -
Symbolic AI for XAI: Evaluating LFIT inductive programming for explaining biases in machine learning
(MDPI, 2021)Machine learning methods are growing in relevance for biometrics and personal information processing in domains such as forensics, e-health, recruitment, and e-learning. In these domains, white-box (human-readable) ... -
Symbolic AI for XAI: Evaluating LFIT Inductive Programming for Explaining Biases in Machine Learning
(Computers, 2021)Machine learning methods are growing in relevance for biometrics and personal information processing in domains such as forensics, e-health, recruitment, and e-learning. In these domains, white-box (human-readable) ...
