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A Comprehensive Feature Study for Appliance Recognition on High Frequency Energy Data.

, , , and . e-Energy, page 121-131. ACM, (2017)

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MEDAL: A Cost-Effective High-Frequency Energy Data Acquisition System for Electrical Appliances., , , and . e-Energy, page 216-221. ACM, (2017)Waveform Signal Entropy and Compression Study of Whole-Building Energy Datasets., , and . e-Energy, page 58-67. ACM, (2019)Waveform Signal Entropy and Compression Study of Whole-Building Energy Datasets., and . CoRR, (2018)Appliance classification across multiple high frequency energy datasets., , , and . SmartGridComm, page 147-152. IEEE, (2017)Appliance Event Detection - A Multivariate, Supervised Classification Approach., , , , and . e-Energy, page 373-375. ACM, (2019)A Comprehensive Feature Study for Appliance Recognition on High Frequency Energy Data., , , and . e-Energy, page 121-131. ACM, (2017)Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery., , , and . Sensors, 15 (11): 27969-27989 (2015)Electrical Appliance Classification using Deep Convolutional Neural Networks on High Frequency Current Measurements., , and . SmartGridComm, page 1-6. IEEE, (2018)CLEAR - A circuit level electric appliance radar for the electric cabinet., , , and . ICIT, page 1130-1135. IEEE, (2017)Methodologies for Distributed Acquisition and Collection of Electrical Energy Data.. Technical University of Munich, Germany, (2019)