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Non-Intrusive Load Monitoring

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Showing 51–99 of 99 papers

TitleStatusHype
Sequence-to-Sequence Model with Transformer-based Attention Mechanism and Temporal Pooling for Non-Intrusive Load Monitoring—0
Subtask Gated Networks for Non-Intrusive Load Monitoring—0
Towards a Deeper Understanding of Transformer for Residential Non-intrusive Load Monitoring—0
Towards Real-world Deployment of NILM Systems: Challenges and Practices—0
Towards trustworthy Energy Disaggregation: A review of challenges, methods and perspectives for Non-Intrusive Load Monitoring—0
Energy Disaggregation & Appliance Identification in a Smart Home: Transfer Learning enables Edge Computing—0
Trimming Feature Extraction and Inference for MCU-based Edge NILM: a Systematic Approach—0
Unsupervised algorithm for disaggregating low-sampling-rate electricity consumption of households—0
Unsupervised Disaggregation of Water Heater Load from Smart Meter Data Processing—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
Non Intrusive Load Monitoring in Chaotic Switching Networks—0
Non-Intrusive Load Monitoring in Smart Grids: A Comprehensive Review—0
Non-Intrusive Load Monitoring (NILM) using Deep Neural Networks: A Review—0
Non-intrusive Load Monitoring via Multi-label Sparse Representation based Classification—0
Non-Intrusive Load Monitoring with Fully Convolutional Networks—0
A PID-Controlled Non-Negative Tensor Factorization Model for Analyzing Missing Data in NILM—0
Online Gaussian LDA for Unsupervised Pattern Mining from Utility Usage Data—0
On the Sensitivity of Deep Load Disaggregation to Adversarial Attacks—0
PowerGAN: Synthesizing Appliance Power Signatures Using Generative Adversarial Networks—0
Preventing Non-intrusive Load Monitoring Privacy Invasion: A Precise Adversarial Attack Scheme for Networked Smart Meters—0
Prior Flow Variational Autoencoder: A density estimation model for Non-Intrusive Load Monitoring—0
A Comprehensive Review on the NILM Algorithms for Energy Disaggregation—0
Privacy Preserving in Non-Intrusive Load Monitoring: A Differential Privacy Perspective—0
Proactive Load-Shaping Strategies with Privacy-Cost Trade-offs in Residential Households based on Deep Reinforcement Learning—0
ProfileSR-GAN: A GAN based Super-Resolution Method for Generating High-Resolution Load Profiles—0
Prompting Large Language Models for Training-Free Non-Intrusive Load Monitoring—0
Quantification of Disaggregation Difficulty with Respect to the Number of Meters—0
Representation Learning for Appliance Recognition: A Comparison to Classical Machine Learning—0
Scale- and Context-Aware Convolutional Non-intrusive Load Monitoring—0
Scaled and Inter-token Relation Enhanced Transformer for Sample-restricted Residential NILM—0
Learning Task-Aware Energy Disaggregation: a Federated ApproachCode0
Towards Comparability in Non-Intrusive Load Monitoring: On Data and Performance EvaluationCode0
On Metrics to Assess the Transferability of Machine Learning Models in Non-Intrusive Load MonitoringCode0
Transfer Learning for Non-Intrusive Load MonitoringCode0
Challenges in Gaussian Processes for Non Intrusive Load MonitoringCode0
Energy Efficient Deep Multi-Label ON/OFF Classification of Low Frequency Metered Home AppliancesCode0
Industrial Energy Disaggregation with Digital Twin-generated Dataset and Efficient Data AugmentationCode0
Few Labels are all you need: A Weakly Supervised Framework for Appliance Localization in Smart-Meter SeriesCode0
Improving Non-Intrusive Load Disaggregation through an Attention-Based Deep Neural NetworkCode0
Toward Explainable NILM: Real-Time Event-Based NILM Framework for High-Frequency DataCode0
Wavenilm: A causal neural network for power disaggregation from the complex power signalCode0
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