3 citations · 3 across the 3 of their papers we have counts for
4 papers
DeepTimeAnomalyViz: A Tool for Visualizing and Post-processing Deep Learning Anomaly Detection Results for Industrial Time-Series
Błażej Leporowski, Casper Hansen, Alexandros Iosifidis
Industrial processes are monitored by a large number of various sensors that produce time-series data. Deep Learning offers a possibility to create anomaly detection methods that c…
Detecting Faults during Automatic Screwdriving: A Dataset and Use Case of Anomaly Detection for Automatic Screwdriving
Błażej Leporowski, Daniella Tola, Casper Hansen +1
Detecting faults in manufacturing applications can be difficult, especially if each fault model is to be engineered by hand. Data-driven approaches, using Machine Learning (ML) for…
Visualising Deep Network's Time-Series Representations
Błażej Leporowski, Alexandros Iosifidis
Despite the popularisation of machine learning models, more often than not, they still operate as black boxes with no insight into what is happening inside the model. There exist a…
AURSAD: Universal Robot Screwdriving Anomaly Detection Dataset
Błażej Leporowski, Daniella Tola, Casper Hansen +1
Screwdriving is one of the most popular industrial processes. As such, it is increasingly common to automate that procedure by using various robots. Even though the automation incr…