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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:

A new approach for optimal time-series segmentation
A. Carmona-Poyato, N.L. Fernández-García, F.J. Madrid-Cuevas, et al.
Pattern Recognition Letters (2020) Vol. 135, pp. 153-159
Open Access | Times Cited: 14

Showing 14 citing articles:

Evolving Elman neural networks based state-of-health estimation for satellite lithium-ion batteries
Dengfeng Zhang, Weichen Li, Xiaodong Han, et al.
Journal of Energy Storage (2023) Vol. 59, pp. 106571-106571
Closed Access | Times Cited: 27
Time series segmentation for recognition of epileptiform patterns recorded via microelectrode arrays in vitro
Gabriel Galeote‐Checa, Gabriella Panuccio, Ángel Canal-Alonso, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0309550-e0309550
Open Access
Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction
Ricardo Petri Silva, Bruno Bogaz Zarpel�ão, Alberto Cano, et al.
Sensors (2021) Vol. 21, Iss. 21, pp. 7333-7333
Open Access | Times Cited: 23
Thanks to repetition, dustbathing detection can be automated combining accelerometry and wavelet analysis
Rocio Guadalupe Fonseca, Maria Candelaria Bosch, Florencia Cecilia Spanevello, et al.
Ethology (2024) Vol. 130, Iss. 7
Open Access | Times Cited: 2
Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning
Parameshwaran Ramalingam, Abolfazl Mehbodniya, Julian Webber, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-10
Open Access | Times Cited: 11
Assessing polygonal approximations: A new measurement and a comparative study
N.L. Fernández-García, Luis Del-Moral Martínez, A. Carmona-Poyato, et al.
Pattern Recognition (2023) Vol. 138, pp. 109396-109396
Open Access | Times Cited: 5
Time series anomaly detection via clustering-based representation
Elham Enayati, Reza Mortazavi, Abdolali Basiri, et al.
Evolving Systems (2023) Vol. 15, Iss. 4, pp. 1115-1136
Closed Access | Times Cited: 3
Adaptive error bounded piecewise linear approximation for time-series representation
Zhou Zhou, Mitra Baratchi, Gangquan Si, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106892-106892
Closed Access | Times Cited: 2
A new approach for optimal offline time-series segmentation with error bound guarantee
A. Carmona-Poyato, N.L. Fernández-García, F.J. Madrid-Cuevas, et al.
Pattern Recognition (2021) Vol. 115, pp. 107917-107917
Closed Access | Times Cited: 5
Impacts of Environmental Factors on Wellbeing: Machine Learning-Based Benchmarking of Spatial and Temporal Properties
Faiza Guerrache, David Brown, Mufti Mahmud
Lecture notes in networks and systems (2024), pp. 631-642
Closed Access
Fault localization using sliding adaptive data segmentation and improved k-nearest neighbour with application to railway track circuits
Shilin Zhao, Chen Guangwu, Peng Li, et al.
Computers & Electrical Engineering (2024) Vol. 122, pp. 109929-109929
Closed Access
Optimal online time-series segmentation
A. Carmona-Poyato, Nicolás-Luis Fernández-García, Francisco-José Madrid-Cuevas, et al.
Knowledge and Information Systems (2023) Vol. 66, Iss. 4, pp. 2417-2438
Closed Access | Times Cited: 1
Feature engineering and long short-term memory for energy use of appliances prediction
I Wayan Aditya Suranata, I Nyoman Kusuma Wardana, Naser Jawas, et al.
TELKOMNIKA (Telecommunication Computing Electronics and Control) (2021) Vol. 19, Iss. 3, pp. 920-920
Open Access | Times Cited: 3
Virtual special issue on novel data-representation and classification techniques
J. Arturo Olvera-López, Joaquín Salas, Jesús Ariel Carrasco-Ochoa, et al.
Pattern Recognition Letters (2020) Vol. 142, pp. 1-2
Closed Access
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