Transfer Learning for Non-Intrusive Load Monitoring

23 February 2019

Papers citing "Transfer Learning for Non-Intrusive Load Monitoring"

15 / 15 papers shown

Title
Energy Efficient Deep Multi-Label ON/OFF Classification of Low Frequency Metered Home Appliances Anže Pirnat Blaž Bertalanič Gregor Cerar M. Mohorčič Carolina Fortuna 27 3 0 18 Jul 2023
Energy Disaggregation & Appliance Identification in a Smart Home: Transfer Learning enables Edge Computing M. Shahab Hasan Mujtaba Buttar Ahsan Mehmood Waqas Aman M. M. U. Rahman M. W. Nawaz H. Pervaiz Q. Abbasi 28 1 0 08 Jan 2023
Towards trustworthy Energy Disaggregation: A review of challenges, methods and perspectives for Non-Intrusive Load Monitoring Maria Kaselimi Eftychios E. Protopapadakis A. Voulodimos N. Doulamis Anastasios Doulamis 24 64 0 05 Jul 2022
DP $^2$ -NILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring Shuang Dai Fanlin Meng Qian Wang Xizhong Chen 23 5 0 30 Jun 2022
Learning Task-Aware Energy Disaggregation: a Federated Approach Ruohong Liu Yize Chen 23 8 0 14 Apr 2022
Dimensionality Expansion of Load Monitoring Time Series and Transfer Learning for EMS Blavz Bertalanivc Jakob Jenko Carolina Fortuna 11 1 0 06 Apr 2022
FederatedNILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring based on Federated Deep Learning Shuang Dai Fanlin Meng Qian Wang Xizhong Chen 28 18 0 08 Aug 2021
FedNILM: Applying Federated Learning to NILM Applications at the Edge Yu Zhang Guoming Tang Qianyi Huang Yi Wang Kui Wu Keping Yu 17 63 0 07 Jun 2021
Energy Disaggregation using Variational Autoencoders A. Langevin M. Carbonneau M. Cheriet G. Gagnon DRL 16 56 0 22 Mar 2021
Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things Jing Zhang Dacheng Tao 45 462 0 17 Nov 2020
A Data-Driven Machine Learning Approach for Consumer Modeling with Load Disaggregation A. K. Zarabie Sanjoy Das Hongyu Wu 6 1 0 04 Nov 2020
Sequence-to-Sequence Load Disaggregation Using Multi-Scale Residual Neural Network Gan Zhou Zhi Li Meng Fu Yanjun Feng Xingyao Wang Chengwei Huang 8 44 0 25 Sep 2020
Exploring Bayesian Surprise to Prevent Overfitting and to Predict Model Performance in Non-Intrusive Load Monitoring Richard Jones Christoph Klemenjak S. Makonin Ivan V. Bajić 6 3 0 16 Sep 2020
Sequence to Point Learning Based on Bidirectional Dilated Residual Network for Non Intrusive Load Monitoring Ziyue Jia Linfeng Yang Zhenrong Zhang Hui Liu Fannie Kong 9 60 0 30 May 2020
On Metrics to Assess the Transferability of Machine Learning Models in Non-Intrusive Load Monitoring Christoph Klemenjak A. Faustine S. Makonin W. Elmenreich 9 16 0 12 Dec 2019