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Non-Intrusive Load Monitoring

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Showing 26–50 of 99 papers

TitleStatusHype
Event Detection for Non-intrusive Load Monitoring using Tukey s Fences—0
Event-driven Two-stage Solution to Non-intrusive Load Monitoring—0
Evolutionary Deep Nets for Non-Intrusive Load Monitoring—0
Exploring Bayesian Surprise to Prevent Overfitting and to Predict Model Performance in Non-Intrusive Load Monitoring—0
FederatedNILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring based on Federated Deep Learning—0
Federated Sequence-to-Sequence Learning for Load Disaggregation from Unbalanced Low-Resolution Smart Meter Data—0
Fed-NILM: A Federated Learning-based Non-Intrusive Load Monitoring Method for Privacy-Protection—0
FedNILM: Applying Federated Learning to NILM Applications at the Edge—0
Functional Intrusive Load Monitor (FILM): A Model-based Platform for Non-Intrusive Load Monitoring System Development—0
HiFAKES: High-frequency synthetic appliance signatures generator for non-intrusive load monitoring—0
IMG-NILM: A Deep learning NILM approach using energy heatmaps—0
Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations—0
Incorporating Coincidental Water Data into Non-intrusive Load Monitoring—0
Latent Tensor Factorization with Nonlinear PID Control for Missing Data Recovery in Non-Intrusive Load Monitoring—0
Low-Frequency Load Identification using CNN-BiLSTM Attention Mechanism—0
Machine Learning Approaches for Non-Intrusive Home Absence Detection Based on Appliance Electrical Use—0
More Behind Your Electricity Bill: a Dual-DNN Approach to Non-Intrusive Load Monitoring—0
MSDC: Exploiting Multi-State Power Consumption in Non-intrusive Load Monitoring based on A Dual-CNN Model—0
Multi Label Restricted Boltzmann Machine for Non-Intrusive Load Monitoring—0
Multi-timescale Event Detection in Nonintrusive Load Monitoring based on MDL Principle—0
Neural Network Ensembles to Real-time Identification of Plug-level Appliance Measurements—0
Non-Intrusive Electrical Appliances Monitoring and Classification using K-Nearest Neighbors—0
Non-Intrusive Load Monitoring Based on Image Load Signatures and Continual Learning—0
Non-intrusive Load Monitoring based on Self-supervised Learning—0
Non-Intrusive Load Monitoring for Feeder-Level EV Charging Detection: Sliding Window-based Approaches to Offline and Online Detection—0
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