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.
Technical Innovation, solving the Data Spaces and Marketplaces Interoperability Problems for the Global Data-Driven Economy
River Publishers
i3-MARKET Series - Part III: The i3-MARKET FOSS Handbook
Systems and Implemented Technologies for Data-Driven Innovation, addressing Data Spaces and Marketplaces Semantic Interoperability Needs
River Publishers
i3-MARKET Series - Part II: Data Economy, Models, Technologies and Solutions
Concepts and Design Innovations addressing the Digital Transformation of Data Spaces and Marketplaces
River Publishers
i3-MARKET Book Series - Part I: A Vision to the future of Data-Driven Economy
3D human big data exchange between the health and garment sectors. Lessons learned in the BodyPass project
BodyPass
3D personal data is a type of data that contains useful information for product design, online sale services, medical research and patient follow-up.
Parallelization and Deployment of Big Data Algorithms: The TOREADOR Approach
32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA). DOI: 10.1109/WAINA.2018.00120
Building the DataBench Workflow and Architecture
International Symposium on Benchmarking, Measuring and Optimization
In the era of Big Data and AI, it is challenging to know all technical and business advantages of the emerging technologies.