Electric current classification with tiny machine learning for home appliances-Reference-Cited by-同舟云学术

Electric current classification with tiny machine learning for home appliances

Published:2022-06-07 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)
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Author:

Pau Danilo¹,Marc Randriatsimiovalaza Dimbiniaina²,Denaro Davide¹

Affiliation:

1. STMicroelectronics, System Research and Applications Agrate Brianza

2. Universita degli studi di Trento,STMicroelectronics

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9831192/9831456/09831563.pdf?arnumber=9831563

Reference20 articles.

1. Improving In-Home Appliance Identification Using Fuzzy-Neighbors-Preserving Analysis Based QR-Decomposition

2. ACS-F2 - A new database of appliance consumption signatures;antonio;2014 6th International Conference of Soft Computing and Pattern Recognition (SoCPaR),2014

3. GREEND: An energy consumption dataset of households in Italy and Austria;andrea;2014 IEEE International Conference on Smart Grid Communications (SmartGridComm),2014

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1. Mel Power Spectrogram Approximation By Tiny Neural Networks for Home Appliances Classification;2023 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT);2023-06-06

2. Coding Mel Spectrogram using Keras and Tensorflow for Home Appliances Tiny Classification;2023 IEEE International Conference on Consumer Electronics (ICCE);2023-01-06

3. Electric Current Classification With Deeply Quantized Neural Network for Home Appliances;2022 International Conference on Information Technology Research and Innovation (ICITRI);2022-11-10