3 citations · 3 across the 1 of their papers we have counts for
2 papers
eess.SP2022★ 3 cited
Representation Learning for Appliance Recognition: A Comparison to Classical Machine Learning
Matthias Kahl, Daniel Jorde, Hans-Arno Jacobsen
Non-intrusive load monitoring (NILM) aims at energy consumption and appliance state information retrieval from aggregated consumption measurements, with the help of signal processi…
cs.OH2019
Appliance Event Detection -- A Multivariate, Supervised Classification Approach
Matthias Kahl, Thomas Kriechbaumer, Daniel Jorde +2
Non-intrusive load monitoring (NILM) is a modern and still expanding technique, helping to understand fundamental energy consumption patterns and appliance characteristics. Applian…