26 citations · 82 across the 9 of their papers we have counts for
9 papers
Enhancing Object Detection Performance for Small Objects through Synthetic Data Generation and Proportional Class-Balancing Technique: A Comparative Study in Industrial Scenarios
Jibinraj Antony, Vinit Hegiste, Ali Nazeri +4
Object Detection (OD) has proven to be a significant computer vision method in extracting localized class information and has multiple applications in the industry. Although many o…
State Derivative Normalization for Continuous-Time Deep Neural Networks
Jonas Weigand, Gerben I. Beintema, Jonas Ulmen +4
The importance of proper data normalization for deep neural networks is well known. However, in continuous-time state-space model estimation, it has been observed that improper nor…
Federated K-Means Clustering via Dual Decomposition-based Distributed Optimization
Vassilios Yfantis, Achim Wagner, Martin Ruskowski
The use of distributed optimization in machine learning can be motivated either by the resulting preservation of privacy or the increase in computational efficiency. On the one han…
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…
Federated Object Detection for Quality Inspection in Shared Production
Vinit Hegiste, Tatjana Legler, Martin Ruskowski
Federated learning (FL) has emerged as a promising approach for training machine learning models on decentralized data without compromising data privacy. In this paper, we propose…
Application of federated learning in manufacturing
Vinit Hegiste, Tatjana Legler, Martin Ruskowski
A vast amount of data is created every minute, both in the private sector and industry. Whereas it is often easy to get hold of data in the private entertainment sector, in the ind…
Small Object Detection for Near Real-Time Egocentric Perception in a Manual Assembly Scenario
Hooman Tavakoli, Snehal Walunj, Parsha Pahlevannejad +2
Detecting small objects in video streams of head-worn augmented reality devices in near real-time is a huge challenge: training data is typically scarce, the input video stream can…
Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game
Nigora Gafur, Gajanan Kanagalingam, Martin Ruskowski
A flexible operation of multiple robotic manipulators in a shared workspace requires an online trajectory planning with static and dynamic collision avoidance. In this work, we pro…
Flatness Based Control of an Industrial Robot Joint Using Secondary Encoders
Jonas Weigand, Nigora Gafur, Martin Ruskowski
Due to their compliant structure, industrial robots without precision-enhancing measures are only to a limited extent suitable for machining applications. Apart from structural, th…