ListarLaboratorio de Investigación e Desenvolvemento en Intelixencia Artificial (LIDIA) por tema "Active learning"
Mostrando ítems 1-4 de 4
-
Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach
(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
(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
(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 ... -
Integrating Iterative Machine Teaching and Active Learning into the Machine Learning Loop
(Elsevier, 2021)[Abstract] Scholars and practitioners are defining new types of interactions between humans and machine learning algorithms that we can group under the umbrella term of Human-in-the-Loop Machine Learning (HITL-ML). This ...
