23 citations · 25 across the 11 of their papers we have counts for
5 papers · 1 filter
The Power of Light: Improving Synthetic-to-Real Domain Adaptation through Physically-Based Indirect Illumination
Hooman Tavakoli Ghinani, Tatjana Legler, Martin Ruskowski
While synthetic data generation resolves the manual labeling bottleneck in computer vision, minimizing the syn-to-real domain gap requires optimizing rendering variables. This pape…
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…
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…
Towards Robust Federated Image Classification: An Empirical Study of Weight Selection Strategies in Manufacturing
Vinit Hegiste, Tatjana Legler, Martin Ruskowski
In the realm of Federated Learning (FL), particularly within the manufacturing sector, the strategy for selecting client weights for server aggregation is pivotal for model perform…
Federated Ensemble YOLOv5 -- A Better Generalized Object Detection Algorithm
Vinit Hegiste, Tatjana Legler, Martin Ruskowski
Federated learning (FL) has gained significant traction as a privacy-preserving algorithm, but the underlying resemblances of federated learning algorithms like Federated averaging…