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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Towards Trustworthy Energy Disaggregation: A Review of Challenges, Methods, and Perspectives for Non-Intrusive Load Monitoring
Maria Kaselimi, Eftychios Protopapadakis, Athanasios Voulodimos, et al.
Sensors (2022) Vol. 22, Iss. 15, pp. 5872-5872
Open Access | Times Cited: 58

Showing 1-25 of 58 citing articles:

An active learning framework for the low-frequency Non-Intrusive Load Monitoring problem
Tamara Todic, Vladimir Stanković, Lina Stanković
Applied Energy (2023) Vol. 341, pp. 121078-121078
Open Access | Times Cited: 32
Performance-Aware NILM Model Optimization for Edge Deployment
Stavros Sykiotis, Sotirios Athanasoulias, Maria Kaselimi, et al.
IEEE Transactions on Green Communications and Networking (2023) Vol. 7, Iss. 3, pp. 1434-1446
Open Access | Times Cited: 19
DeepEdge-NILM: A case study of non-intrusive load monitoring edge device in commercial building
R. Gopinath, Mukesh Kumar
Energy and Buildings (2023) Vol. 294, pp. 113226-113226
Closed Access | Times Cited: 14
Detection of Anomalies in Daily Activities Using Data from Smart Meters
Álvaro Hernández, Rubén Nieto, Laura de Diego-Otón, et al.
Sensors (2024) Vol. 24, Iss. 2, pp. 515-515
Open Access | Times Cited: 5
Non-Intrusive Load Monitoring in industrial settings: A systematic review
Giulia Tanoni, Emanuele Principi, Stefano Squartini
Renewable and Sustainable Energy Reviews (2024) Vol. 202, pp. 114703-114703
Open Access | Times Cited: 5
Review of Transition from Mining 4.0 to 5.0 in Fossil Energy Sources Production
Sergey Zhironkin, Elena Dotsenko
Energies (2023) Vol. 16, Iss. 15, pp. 5794-5794
Open Access | Times Cited: 13
Neural Load Disaggregation: Meta-Analysis, Federated Learning and Beyond
Hafsa Bousbiat, Yassine Himeur, Iraklis Varlamis, et al.
Energies (2023) Vol. 16, Iss. 2, pp. 991-991
Open Access | Times Cited: 12
A Semi-Supervised Approach for Improving Generalization in Non-Intrusive Load Monitoring
Dea Pujić, Nikola Tomašević, Marko Batić
Sensors (2023) Vol. 23, Iss. 3, pp. 1444-1444
Open Access | Times Cited: 11
The Plegma dataset: Domestic appliance-level and aggregate electricity demand with metadata from Greece
Sotirios Athanasoulias, Fernanda Guasselli, Nikolaos Doulamis, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 4
Application of improved DBN and GRU based on intelligent optimization algorithm in power load identification and prediction
Jintao Wu, Xiling Tang, Dongxu Zhou, et al.
Energy Informatics (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 3
Real-Time Detection and Classification of Power Quality Disturbances
Mahsa Mozaffari, Keval Doshi, Yasin Yılmaz
Sensors (2022) Vol. 22, Iss. 20, pp. 7958-7958
Open Access | Times Cited: 20
A versatile, low-cost monitoring device suitable for non-intrusive load monitoring research purposes
Sarantis Kotsilitis, Effie Marcoulaki, Emmanouil Kalligeros
Measurement Sensors (2024) Vol. 32, pp. 101081-101081
Open Access | Times Cited: 2
A Survey on the Use of Synthetic Data for Enhancing Key Aspects of Trustworthy AI in the Energy Domain: Challenges and Opportunities
Michael Meiser, Ingo Zinnikus
Energies (2024) Vol. 17, Iss. 9, pp. 1992-1992
Open Access | Times Cited: 2
Improving Knowledge Distillation for Non-Intrusive Load Monitoring Through Explainability Guided Learning
Djordje Batic, Giulia Tanoni, Lina Stanković, et al.
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2023), pp. 1-5
Open Access | Times Cited: 7
Toward Transparent Load Disaggregation—A Framework for Quantitative Evaluation of Explainability Using Explainable AI
Djordje Batic, Vladimir Stanković, Lina Stanković
IEEE Transactions on Consumer Electronics (2023) Vol. 70, Iss. 1, pp. 4345-4356
Open Access | Times Cited: 7
Appliance Detection Using Very Low-Frequency Smart Meter Time Series
Adrien Petralia, Philippe Charpentier, Paul Boniol, et al.
(2023), pp. 214-225
Open Access | Times Cited: 6
Non-Intrusive Load State Monitoring Through Smart Meter ‎Disaggregation Using 1d Deep ‎Reconstruction Networks
Sakib Mahmud, Mahdi Houchati, Fayçal Bensaali, et al.
(2024)
Closed Access | Times Cited: 1
Adaptive Knowledge Sharing in Multi-Task Learning: Insights from Electricity Data Analysis
Yu-Hsiang Chang, Lo Pang-Yun Ting, Wei-Cheng Yin, et al.
Lecture notes in computer science (2024), pp. 148-160
Closed Access | Times Cited: 1
Human in the loop active learning for time-series electrical measurement data
Tamara Sobot, Vladimir Stanković, Lina Stanković
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108589-108589
Open Access | Times Cited: 1
A VMD-deep learning approach for individual load monitoring and forecasting for residential buildings energy management
Ismael Jrhilifa, Hamid Ouadi, Abdelilah Jilbab, et al.
e-Prime - Advances in Electrical Engineering Electronics and Energy (2024) Vol. 8, pp. 100624-100624
Open Access | Times Cited: 1
Comparing four machine learning algorithms for household non-intrusive load monitoring
Thomas Lee Young, James Gopsill, Maria Valero, et al.
Energy and AI (2024) Vol. 17, pp. 100384-100384
Open Access | Times Cited: 1
Energy Disaggregation of Industrial Machinery Utilizing Artificial Neural Networks for Non-intrusive Load Monitoring
Philipp Pelger, Johannes Steinleitner, Alexander Sauer
Energy and AI (2024) Vol. 17, pp. 100407-100407
Open Access | Times Cited: 1
Explainability-Informed Feature Selection and Performance Prediction for Nonintrusive Load Monitoring
Rachel Stephen Mollel, Lina Stanković, Vladimir Stanković
Sensors (2023) Vol. 23, Iss. 10, pp. 4845-4845
Open Access | Times Cited: 4
Contextual Sequence-to-Point Deep Learning for Household Energy Disaggregation
Mohammed Ayub, El-Sayed M. El-Alfy
IEEE Access (2023) Vol. 11, pp. 75599-75616
Open Access | Times Cited: 4
Generation of meaningful synthetic sensor data — Evaluated with a reliable transferability methodology
Michael Meiser, Benjamin Duppe, Ingo Zinnikus
Energy and AI (2023) Vol. 15, pp. 100308-100308
Open Access | Times Cited: 4
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