Home appliance power ‘sensed’ at high accuracy with tiny datasets (IMAGE)

University of Johannesburg

Home appliance power ‘sensed’ at high accuracy with tiny datasets

Caption

Researchers from the University of Johannesburg tested a Few Shot Learning (FSL) algorithm for recognizing home appliance power signals. As the number of testing images increases, the average accuracy increases from a minimum of 91.343% to a maximum of 97.83%.

Credit

Credit: Liston Matindife and Therese van Wyk. Data from study in Computational Intelligence and Neuroscience. (https://doi.org/10.1155/2022/2142935 ) (https://creativecommons.org/licenses/by/4.0/

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