Abstract: Hierarchical Federated Learning (HFL) has emerged as a promising paradigm for distributed machine learning in edge computing environments. By introducing intermediate edge servers between ...
New digital platform combines regulatory intelligence, food safety analytics and AI-driven risk detection With SGS ...
Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...
Principal Architect Sandeep Patil’s landmark research charts a new course for cloud-native data warehousing — from serverless MPP engines and lakehouse convergence to AI-powered query optimization and ...
Discover how a new AI system is revolutionizing energy management by merging machine learning and mathematical programming. This innovative approach not only boosts prediction accuracy but also ...
Utilities worldwide are turning to artificial intelligence (AI) and machine learning to stabilize networks, forecast consumption, detect faults, and optimize system performance in real-time. What was ...
Earth observation (EO) constellations capture huge volumes of high-resolution imagery every day, but most of it never reaches the ground in time for model training. Downlink bandwidth is the main ...
The field of medicine and medical imaging (X-rays, MRIs, CT scans, etc.) is rich in data, creating fertile ground for Artificial Intelligence (AI). Machine learning models, particularly deep neural ...
Abstract: A method for distributed polarization mode dispersion (PMD) measurement based on machine learning assisted POTDR is presented in this study, which extracts the characteristics of ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results