Summary

Vinit Hegiste studied Bachelors of Engineering (B.Eng) in Electronics and Telecommunication from Mumbai University. As part of his bachelor thesis, he worked on mammogram classification based on an ensemble classification method. He moved to Saarbrücken in 2018 to pursue a Master's in Computer Science (M.Sc) from Universität des Saarlandes. His master thesis topic was ‘Gesture controlled mobile robot in warehouse and retail scenarios’, where he dealt with developing an algorithm to recognize gestures and body pose using a static RGB camera (without any wearables). Since May 2021, he has been working as Research Assistant at the Chair of Machine Tools and Control Systems.

Research Fields

AI in manufacturing using computer vision and federated learning

Publications

ORCID

V. Hegiste, T. Legler, and M. Ruskowski. "Towards robust federated image classification: An empirical study of weight selection strategies in manufacturing." 2024 2nd International Conference on Federated Learning Technologies and Applications (FLTA). IEEE, 2024. Link

V. Hegiste, T. Legler,  and M. Ruskowski. (2024, October). Collaborative learning in shared production environment using federated image classification. In European Symposium on Artificial Intelligence in Manufacturing (pp. 98-106). Cham: Springer Nature Switzerland. Link

V. Hegiste, S. Walunj, J. Antony, T. Legler, and M. Ruskowski (2024, May). Enhancing object detection with hybrid dataset in manufacturing environments: Comparing federated learning to conventional techniques. In 2024 1st International Conference on Innovative Engineering Sciences and Technological Research (ICIESTR) (pp. 1-6). IEEE. Link

V. Hegiste, T. Legler and M. Ruskowski, Federated Ensemble YOLOv5 – A Better Generalized Object Detection Algorithm, 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), Tartu, Estonia, 2023, pp. 7-14. Link

V. Hegiste, T. Legler, K. Fridman and M. Ruskowski, Federated Object Detection for Quality Inspection in Shared Production, 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), Tartu, Estonia, pp. 151-158. Link

V. Hegiste, T. Legler and M. Ruskowski, Application of Federated Machine Learning in Manufacturing, 2022. International Conference on Industry 4.0 Technology (I4Tech), 1-8.  Link