4 papers
Federated Action Recognition for Smart Worker Assistance Using FastPose
Vinit Hegiste, Vidit Goyal, Tatjana Legler +1
In smart manufacturing environments, accurate and real-time recognition of worker actions is essential for productivity, safety, and human-machine collaboration. While skeleton-bas…
Seamless Integration: Sampling Strategies in Federated Learning Systems
Tatjana Legler, Vinit Hegiste, Martin Ruskowski
Federated Learning (FL) represents a paradigm shift in the field of machine learning, offering an approach for a decentralized training of models across a multitude of devices whil…
Addressing Heterogeneity in Federated Learning: Challenges and Solutions for a Shared Production Environment
Tatjana Legler, Vinit Hegiste, Ahmed Anwar +1
Federated learning (FL) has emerged as a promising approach to training machine learning models across decentralized data sources while preserving data privacy, particularly in man…
Enhancing Object Detection with Hybrid dataset in Manufacturing Environments: Comparing Federated Learning to Conventional Techniques
Vinit Hegiste, Snehal Walunj, Jibinraj Antony +2
Federated Learning (FL) has garnered significant attention in manufacturing for its robust model development and privacy-preserving capabilities. This paper contributes to research…