Benjamin Maschler | DeepAI

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∙ 01/04/2023

A Survey on Deep Industrial Transfer Learning in Fault Prognostics

Due to its probabilistic nature, fault prognostics is a prime example of...

0 Benjamin Maschler, et al. ∙

∙ 07/04/2022

Intelligent Exploration of Solution Spaces Exemplified by Industrial Reconfiguration Management

Many decision-making approaches rely on the exploration of solution spac...

0 Timo Müller, et al. ∙

∙ 04/04/2022

Stuttgart Open Relay Degradation Dataset (SOReDD)

Real-life industrial use cases for machine learning oftentimes involve h...

0 Benjamin Maschler, et al. ∙

∙ 04/04/2022

Towards Deep Industrial Transfer Learning: Clustering for Transfer Case Selection

Industrial transfer learning increases the adaptability of deep learning...

0 Benjamin Maschler, et al. ∙

∙ 07/07/2021

Regularization-based Continual Learning for Fault Prediction in Lithium-Ion Batteries

In recent years, the use of lithium-ion batteries has greatly expanded i...

0 Benjamin Maschler, et al. ∙

∙ 06/30/2021

Towards establishing formal verification and inductive code synthesis in the PLC domain

Nowadays, formal methods are used in various areas for the verification ...

0 Matthias Weiß, et al. ∙

∙ 06/09/2021

Towards Deep Industrial Transfer Learning for Anomaly Detection on Time Series Data

Deep learning promises performant anomaly detection on time-variant data...

0 Benjamin Maschler, et al. ∙

∙ 05/31/2021

Transfer Learning as an Enhancement for Reconfiguration Management of Cyber-Physical Production Systems

Reconfiguration demand is increasing due to frequent requirement changes...

0 Benjamin Maschler, et al. ∙

∙ 05/28/2021

A Survey on Anomaly Detection for Technical Systems using LSTM Networks

Anomalies represent deviations from the intended system operation and ca...

0 Benjamin Lindemann, et al. ∙

∙ 01/02/2021

Regularization-based Continual Learning for Anomaly Detection in Discrete Manufacturing

The early and robust detection of anomalies occurring in discrete manufa...

0 Benjamin Maschler, et al. ∙

∙ 12/06/2020

Deep Transfer Learning for Industrial Automation: A Review and Discussion of New Techniques for Data-Driven Machine Learning

In this article, the concepts of transfer and continual learning are int...

25 Benjamin Maschler, et al. ∙

∙ 12/03/2020

Transfer Learning as an Enabler of the Intelligent Digital Twin

Digital Twins have been described as beneficial in many areas, such as v...

0 Benjamin Maschler, et al. ∙

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