Scattering Transform for Classification in Non-Intrusive Load Monitoring
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- Qian Wu & Fei Wang, 2019. "Concatenate Convolutional Neural Networks for Non-Intrusive Load Monitoring across Complex Background," Energies, MDPI, vol. 12(8), pages 1-17, April.
- Anthony Faustine & Lucas Pereira, 2020. "Multi-Label Learning for Appliance Recognition in NILM Using Fryze-Current Decomposition and Convolutional Neural Network," Energies, MDPI, vol. 13(16), pages 1-17, August.
- Christos Athanasiadis & Dimitrios Doukas & Theofilos Papadopoulos & Antonios Chrysopoulos, 2021. "A Scalable Real-Time Non-Intrusive Load Monitoring System for the Estimation of Household Appliance Power Consumption," Energies, MDPI, vol. 14(3), pages 1-23, February.
- Patrick Huber & Alberto Calatroni & Andreas Rumsch & Andrew Paice, 2021. "Review on Deep Neural Networks Applied to Low-Frequency NILM," Energies, MDPI, vol. 14(9), pages 1-34, April.
- Antonio Ruano & Alvaro Hernandez & Jesus Ureña & Maria Ruano & Juan Garcia, 2019. "NILM Techniques for Intelligent Home Energy Management and Ambient Assisted Living: A Review," Energies, MDPI, vol. 12(11), pages 1-29, June.
- Douglas Paulo Bertrand Renaux & Fabiana Pottker & Hellen Cristina Ancelmo & André Eugenio Lazzaretti & Carlos Raiumundo Erig Lima & Robson Ribeiro Linhares & Elder Oroski & Lucas da Silva Nolasco & Lu, 2020. "A Dataset for Non-Intrusive Load Monitoring: Design and Implementation," Energies, MDPI, vol. 13(20), pages 1-35, October.
- Saura, José Ramón & Palacios-Marqués, Daniel & Iturricha-Fernández, Agustín, 2021. "Ethical design in social media: Assessing the main performance measurements of user online behavior modification," Journal of Business Research, Elsevier, vol. 129(C), pages 271-281.
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- Yongtao Shi & Xiaodong Zhao & Fan Zhang & Yaguang Kong, 2022. "Non-Intrusive Load Monitoring Based on Swin-Transformer with Adaptive Scaling Recurrence Plot," Energies, MDPI, vol. 15(20), pages 1-18, October.
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Keywords
scattering transform; NILM features; features extractor;All these keywords.
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