Listar Laboratorio de Investigación e Desenvolvemento en Intelixencia Artificial (LIDIA) por autor "Bobes-Bascarán, José"
Mostrando ítems 1-4 de 4
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A classification and review of tools for developing and interacting with machine learning systems
Mosqueira-Rey, E.; Hernández-Pereira, Elena; Alonso Ríos, David; Bobes-Bascarán, José (Association for Computing Machinery, 2022)[Abstract] In this paper we aim to bring some order to the myriad of tools that have emerged in the field of Artificial Intelligence (AI), focusing on the field of Machine Learning (ML). For this purpose, we suggest a ... -
Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach
Mosqueira-Rey, E.; Hernández-Pereira, Elena; Bobes-Bascarán, José; Alonso Ríos, David; Pérez-Sánchez, Alberto; Fernández-Leal, Ángel; Moret-Bonillo, Vicente; Vidal-Ínsua, Yolanda; Vázquez-Rivera, Francisca (Springer Nature, 2023-11)[Abstract]: Any machine learning (ML) model is highly dependent on the data it uses for learning, and this is even more important in the case of deep learning models. The problem is a data bottleneck, i.e. the difficulty ... -
Human-in-the-loop machine learning: a state of the art
Mosqueira-Rey, E.; Hernández-Pereira, Elena; Alonso Ríos, David; Bobes-Bascarán, José; Fernández-Leal, Ángel (Springer Nature, 2023-04)[Abstract]: Researchers are defining new types of interactions between humans and machine learning algorithms generically called human-in-the-loop machine learning. Depending on who is in control of the learning process, ... -
Improving Medical Data Annotation Including Humans in the Machine Learning Loop
Bobes-Bascarán, José; Mosqueira-Rey, E.; Alonso Ríos, David (MDPI, 2021)[Abstract] At present, the great majority of Artificial Intelligence (AI) systems require the participation of humans in their development, tuning, and maintenance. Particularly, Machine Learning (ML) systems could greatly ...