2 citations · 3 across the 5 of their papers we have counts for
5 papers · 1 filter
Autoencoder based Anomaly Detection and Explained Fault Localization in Industrial Cooling Systems
Stephanie Holly, Robin Heel, Denis Katic +8
Anomaly detection in large industrial cooling systems is very challenging due to the high data dimensionality, inconsistent sensor recordings, and lack of labels. The state of the…
Smart Active Sampling to enhance Quality Assurance Efficiency
Clemens Heistracher, Stefan Stricker, Pedro Casas +2
We propose a new sampling strategy, called smart active sapling, for quality inspections outside the production line. Based on the principles of active learning a machine learning…
Evaluation of Hyperparameter-Optimization Approaches in an Industrial Federated Learning System
Stephanie Holly, Thomas Hiessl, Safoura Rezapour Lakani +3
Federated Learning (FL) decouples model training from the need for direct access to the data and allows organizations to collaborate with industry partners to reach a satisfying le…
Minimal-Configuration Anomaly Detection for IIoT Sensors
Clemens Heistracher, Anahid Jalali, Axel Suendermann +4
The increasing deployment of low-cost IoT sensor platforms in industry boosts the demand for anomaly detection solutions that fulfill two key requirements: minimal configuration ef…
Towards Robust and Transferable IIoT Sensor based Anomaly Classification using Artificial Intelligence
Jana Kemnitz, Thomas Bierweiler, Herbert Grieb +2
The increasing deployment of low-cost industrial IoT (IIoT) sensor platforms on industrial assets enables great opportunities for anomaly classification in industrial plants. The p…