Preserving data privacy in Machine Learning pipelines with Federated Learning
FAME's project blog
The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.
Real-time Probabilistic Data Fusion for Large-scale IoT Applications
IEEE Access, vol. PP, no. 99, pp. 1-1. DOI: 10.1109/ACCESS.2018.2804623
Real-time Probabilistic Data Fusion for Large-scale IoT Applications
IEEE Access, vol. PP, no. 99, pp. 1-1. doi: 10.1109/ACCESS.2018.2804623
An integrated information lifecycle management framework for exploiting social network data to identify dynamic large crowd concentration events in smart cities applications
Future Generation Computer Systems, 2017
Volume 78, Part 2