Listarvol. 9, nº 3, june 2025 por tema "Deep Learning"
Mostrando ítems 1-3 de 3
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Large Language Models for in Situ Knowledge Documentation and Access With Augmented Reality
(UNIR, 01/06/2025)Augmented reality (AR) has become a powerful tool for assisting operators in complex environments, such as shop floors, laboratories, and industrial settings. By displaying synthetic visual elements anchored in real ... -
Stacked LSTM for Short-Term Wind Power Forecasting Using Multivariate Time Series Data
(UNIR, 01/06/2025)Currently, wind power is the fast growing area in the domain of renewable energy generation. Accurate prediction of wind power output in wind farms is crucial for addressing the challenges associated the power grid. This ... -
Testing Deep Learning Recommender Systems Models on Synthetic GAN-Generated Datasets
(UNIR, 01/06/2025)The published method Generative Adversarial Networks for Recommender Systems (GANRS) allows generating data sets for collaborative filtering recommendation systems. The GANRS source code is available along with a representative ...
