Patrick Marques Ciarelli

702 total citations
60 papers, 451 citations indexed

About

Patrick Marques Ciarelli is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Mechanical Engineering. According to data from OpenAlex, Patrick Marques Ciarelli has authored 60 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 10 papers in Mechanical Engineering. Recurrent topics in Patrick Marques Ciarelli's work include Text and Document Classification Technologies (12 papers), Anomaly Detection Techniques and Applications (7 papers) and Face and Expression Recognition (6 papers). Patrick Marques Ciarelli is often cited by papers focused on Text and Document Classification Technologies (12 papers), Anomaly Detection Techniques and Applications (7 papers) and Face and Expression Recognition (6 papers). Patrick Marques Ciarelli collaborates with scholars based in Brazil, United Kingdom and Mongolia. Patrick Marques Ciarelli's co-authors include Elias Oliveira, Evandro Ottoni Teatini Salles, Celso J. Munaro, Alberto F. De Souza, Claudine Badué, Lucas Veronese, Rodolfo da Silva Villaça, Moisés R. N. Ribeiro, Luís C. B. Silva and Jussara Farias Fardin and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Patrick Marques Ciarelli

55 papers receiving 427 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Patrick Marques Ciarelli Brazil 12 210 102 65 50 50 60 451
Paulo Martins Engel Brazil 11 207 1.0× 167 1.6× 83 1.3× 62 1.2× 25 0.5× 52 500
Magnus Pedersen United Kingdom 4 127 0.6× 60 0.6× 57 0.9× 24 0.5× 37 0.7× 12 405
Ho-Sung Park South Korea 12 272 1.3× 45 0.4× 48 0.7× 42 0.8× 17 0.3× 38 452
Jonathan Lee Taiwan 13 163 0.8× 83 0.8× 106 1.6× 49 1.0× 12 0.2× 52 410
Xiao-Zhi Gao Finland 13 261 1.2× 54 0.5× 81 1.2× 39 0.8× 17 0.3× 38 482
Zhe Yu China 2 224 1.1× 52 0.5× 37 0.6× 33 0.7× 19 0.4× 3 451
Masumi Ishikawa Japan 10 284 1.4× 92 0.9× 60 0.9× 18 0.4× 17 0.3× 49 448

Countries citing papers authored by Patrick Marques Ciarelli

Since Specialization
Citations

This map shows the geographic impact of Patrick Marques Ciarelli's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Patrick Marques Ciarelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Marques Ciarelli more than expected).

Fields of papers citing papers by Patrick Marques Ciarelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Patrick Marques Ciarelli. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Patrick Marques Ciarelli. The network helps show where Patrick Marques Ciarelli may publish in the future.

Co-authorship network of co-authors of Patrick Marques Ciarelli

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick Marques Ciarelli. A scholar is included among the top collaborators of Patrick Marques Ciarelli based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Patrick Marques Ciarelli. Patrick Marques Ciarelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Munaro, Celso J., et al.. (2025). Enhancing one-Class classifiers performance in multivariate time series through dynamic clustering: A case study on hydraulic system fault detection. Expert Systems with Applications. 286. 128088–128088. 1 indexed citations
2.
Oliveira, Luiz S., et al.. (2025). A Somatotype Classification Approach Based on Generative AI and Frontal Images of Individuals. IEEE Access. 13. 52939–52948.
3.
Goulart, Elisa Valentim, et al.. (2025). Spatial patterns of probability distributions for concentration fluctuations at the street network scale. Building and Environment. 285. 113491–113491.
4.
Fardin, Jussara Farias, et al.. (2023). Conventional Dissolved Gases Analysis in Power Transformers: Review. Energies. 16(21). 7219–7219. 9 indexed citations
5.
Munaro, Celso J., et al.. (2023). Time series clustering to improve one-class classifier performance. Expert Systems with Applications. 243. 122895–122895. 5 indexed citations
6.
Ciarelli, Patrick Marques, et al.. (2023). Identifying ADHD and subtypes through microstates analysis and complex networks. Medical & Biological Engineering & Computing. 62(3). 687–700. 6 indexed citations
7.
8.
Salles, Evandro Ottoni Teatini, et al.. (2021). A New Approach to Enhanced Swarm Intelligence Applied to Video Target Tracking. Sensors. 21(5). 1903–1903. 6 indexed citations
9.
Ciarelli, Patrick Marques, et al.. (2021). Automatic Identification of Somatotype by Digital Images.
10.
Silva, Luís C. B., Patrick Marques Ciarelli, Jean Carlos Cardozo da Silva, et al.. (2020). Detection of Multiple Small Temperature Events Simultaneously on a Distributed Temperature Map. IEEE Sensors Journal. 21(4). 4582–4589. 14 indexed citations
11.
Salles, Evandro Ottoni Teatini, et al.. (2020). Fast Deep Stacked Networks based on Extreme Learning Machine applied to regression problems. Neural Networks. 131. 14–28. 11 indexed citations
12.
Salles, Evandro Ottoni Teatini, et al.. (2019). Outlier Robust Extreme Machine Learning for multi-target regression. Expert Systems with Applications. 140. 112877–112877. 29 indexed citations
13.
Ciarelli, Patrick Marques, et al.. (2019). Feature extraction in an ensemble of multiple local classifiers for fault diagnosis in industrial processes. IFAC-PapersOnLine. 52(1). 293–298. 2 indexed citations
14.
Ciarelli, Patrick Marques, et al.. (2019). Industrial Optical Character Recognition System in Printing Quality Control of Hot-Rolled Coils Identification. Journal of Control Automation and Electrical Systems. 31(1). 108–118. 19 indexed citations
15.
Ciarelli, Patrick Marques, et al.. (2019). Novelty Detection in Social Media by Fusing Text and Image Into a Single Structure. IEEE Access. 7. 132786–132802. 5 indexed citations
16.
Salles, Evandro Ottoni Teatini, et al.. (2018). Modification in the SAR Super-Resolution Model Using the Fractal Descriptor LMME in the Term Regularizer. IEEE Access. 6. 39046–39062. 1 indexed citations
17.
Salles, Evandro Ottoni Teatini, et al.. (2018). Texture Representation and Classification with Artificial Hikers and Fractals. 19. 1–8. 1 indexed citations
18.
Ciarelli, Patrick Marques, et al.. (2017). O sentimento político em redes sociais. SHILAP Revista de lepidopterología. 13(2). e4089–e4089. 5 indexed citations
19.
Ciarelli, Patrick Marques, Elias Oliveira, & Evandro Ottoni Teatini Salles. (2013). Multi-label incremental learning applied to web page categorization. Neural Computing and Applications. 24(6). 1403–1419. 13 indexed citations
20.
Ciarelli, Patrick Marques, Elias Oliveira, & Evandro Ottoni Teatini Salles. (2012). An incremental neural network with a reduced architecture. Neural Networks. 35. 70–81. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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