5 citations · 5 across the 4 of their papers we have counts for
4 papers
Continual Learning of Domain-Invariant Representations
Pascal Janetzky, Tobias Schlagenhauf, Stefan Feuerriegel
Continual learning (CL) aims to train models sequentially over multiple domains without forgetting previously learned knowledge. However, existing CL methods optimize for in-domain…
Slowing Down Forgetting in Continual Learning
Pascal Janetzky, Tobias Schlagenhauf, Stefan Feuerriegel
A common challenge in continual learning (CL) is catastrophic forgetting, where the performance on old tasks drops after new, additional tasks are learned. In this paper, we propos…
Discriminative Feature Learning through Feature Distance Loss
Tobias Schlagenhauf, Yiwen Lin, Benjamin Noack
Ensembles of Convolutional neural networks have shown remarkable results in learning discriminative semantic features for image classification tasks. Though, the models in the ense…
Intelligent Vision Based Wear Forecasting on Surfaces of Machine Tool Elements
Tobias Schlagenhauf, Niklas Burghardt
This paper addresses the ability to enable machines to automatically detect failures on machine tool components as well as estimating the severity of the failures, which is a criti…