2 citations · 2 across the 1 of their papers we have counts for
2 papers
cs.LG2024★ 2 cited
Federated Learning for Traffic Flow Prediction with Synthetic Data Augmentation
Fermin Orozco, Pedro Porto Buarque de Gusmão, Hongkai Wen +2
Deep-learning based traffic prediction models require vast amounts of data to learn embedded spatial and temporal dependencies. The inherent privacy and commercial sensitivity of s…
eess.SP2019
Sensor Fusion for Magneto-Inductive Navigation
Johan Wahlström, Manon Kok, Pedro Porto Buarque de Gusmao +3
Magneto-inductive navigation is an inexpensive and easily deployable solution to many of today's navigation problems. By utilizing very low frequency magnetic fields, magneto-induc…