Nemesyst: A Hybrid Parallelism Deep Learning-Based Framework Applied for Internet of Things Enabled Food Retailing Refrigeration Systems

4 June 2019

Papers citing "Nemesyst: A Hybrid Parallelism Deep Learning-Based Framework Applied for Internet of Things Enabled Food Retailing Refrigeration Systems"

7 / 7 papers shown

Title
Tabular Machine Learning Methods for Predicting Gas Turbine Emissions Rebecca Potts R. Hackney Georgios Leontidis 27 3 0 17 Jul 2023
Model Pruning Enables Localized and Efficient Federated Learning for Yield Forecasting and Data Sharing An-dong Li Milan Markovic P. Edwards Georgios Leontidis FedML 35 16 0 19 Apr 2023
EDLaaS: Fully Homomorphic Encryption Over Neural Network Graphs for Vision and Private Strawberry Yield Forecasting George Onoufriou Marc Hanheide Georgios Leontidis FedML 24 4 0 26 Oct 2021
AI-enabled Efficient and Safe Food Supply Chain I. Kollia J. Stevenson Stefanos D. Kollias 19 30 0 01 May 2021
The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector A. Durrant Milan Markovic David Matthews David May J. Enright Georgios Leontidis FedML 32 69 0 14 Apr 2021
A Hybrid Parallelization Approach for Distributed and Scalable Deep Learning S. Akintoye Liangxiu Han Xin Zhang Haoming Chen Daoqiang Zhang 30 15 0 11 Apr 2021
Multi-Source Deep Domain Adaptation for Quality Control in Retail Food Packaging Mamatha Thota Stefanos D. Kollias M. Swainson Georgios Leontidis 22 4 0 28 Jan 2020