José Ruiz-Pinales

739 total citations
55 papers, 473 citations indexed

About

José Ruiz-Pinales is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, José Ruiz-Pinales has authored 55 papers receiving a total of 473 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 11 papers in Cognitive Neuroscience and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in José Ruiz-Pinales's work include EEG and Brain-Computer Interfaces (8 papers), Handwritten Text Recognition Techniques (7 papers) and ECG Monitoring and Analysis (5 papers). José Ruiz-Pinales is often cited by papers focused on EEG and Brain-Computer Interfaces (8 papers), Handwritten Text Recognition Techniques (7 papers) and ECG Monitoring and Analysis (5 papers). José Ruiz-Pinales collaborates with scholars based in Mexico, Spain and France. José Ruiz-Pinales's co-authors include Juan Gabriel Avina‐Cervantes, Ivan Cruz‐Aceves, Sergio Ledesma, M. Torres‐Cisneros, Rafael Guzmán-Cabrera, Éric Lecolinet, Oscar Ibarra‐Manzano, Jorge M. Cruz‐Duarte, Horacio Rostro‐González and María José Castro-Bleda and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

José Ruiz-Pinales

49 papers receiving 450 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
José Ruiz-Pinales Mexico 13 150 143 135 69 56 55 473
Fardin Abdali-Mohammadi Iran 15 66 0.4× 187 1.3× 135 1.0× 163 2.4× 36 0.6× 44 573
Roberto Rigamonti Switzerland 8 102 0.7× 413 2.9× 123 0.9× 14 0.2× 40 0.7× 10 548
Quan Zhou China 11 56 0.4× 143 1.0× 50 0.4× 16 0.2× 107 1.9× 57 406
René Grzeszick Germany 7 92 0.6× 279 2.0× 131 1.0× 13 0.2× 15 0.3× 17 429
Yingle Fan China 10 75 0.5× 155 1.1× 137 1.0× 91 1.3× 23 0.4× 48 364
S.B. Gokturk United States 11 150 1.0× 601 4.2× 122 0.9× 14 0.2× 50 0.9× 18 874
Imtiaz Ahmad Taj Pakistan 13 46 0.3× 299 2.1× 66 0.5× 12 0.2× 59 1.1× 64 520
Loc Tran United States 10 139 0.9× 161 1.1× 147 1.1× 33 0.5× 16 0.3× 37 498
Yuhao Luo China 14 119 0.8× 112 0.8× 49 0.4× 18 0.3× 178 3.2× 41 518
Mostafa E. A. Ibrahim Egypt 10 79 0.5× 118 0.8× 62 0.5× 14 0.2× 55 1.0× 29 343

Countries citing papers authored by José Ruiz-Pinales

Since Specialization
Citations

This map shows the geographic impact of José Ruiz-Pinales'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 José Ruiz-Pinales with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites José Ruiz-Pinales more than expected).

Fields of papers citing papers by José Ruiz-Pinales

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José Ruiz-Pinales. 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 José Ruiz-Pinales. The network helps show where José Ruiz-Pinales may publish in the future.

Co-authorship network of co-authors of José Ruiz-Pinales

This figure shows the co-authorship network connecting the top 25 collaborators of José Ruiz-Pinales. A scholar is included among the top collaborators of José Ruiz-Pinales 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 José Ruiz-Pinales. José Ruiz-Pinales 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.
Ibarra-Manzano, Mario-Alberto, et al.. (2025). Retinal Vessel Segmentation Based on a Lightweight U-Net and Reverse Attention. Mathematics. 13(13). 2203–2203. 1 indexed citations
2.
Ibarra-Manzano, Mario-Alberto, et al.. (2024). Brain Tumor Segmentation from Optimal MRI Slices Using a Lightweight U-Net. SHILAP Revista de lepidopterología. 12(10). 183–183. 2 indexed citations
3.
4.
Avina‐Cervantes, Juan Gabriel, et al.. (2023). Motor Imagery Multi-Tasks Classification for BCIs Using the NVIDIA Jetson TX2 Board and the EEGNet Network. Sensors. 23(8). 4164–4164. 2 indexed citations
5.
Avina‐Cervantes, Juan Gabriel, et al.. (2023). Quantum angle encoding with learnable rotation applied to quantum–classical convolutional neural networks. Applied Soft Computing. 141. 110307–110307. 22 indexed citations
6.
Avina‐Cervantes, Juan Gabriel, et al.. (2022). LRSE-Net: Lightweight Residual Squeeze-and-Excitation Network for Stenosis Detection in X-ray Coronary Angiography. Electronics. 11(21). 3570–3570. 10 indexed citations
7.
Ruiz-Pinales, José, et al.. (2022). Use of image processing for the detection of Parkinson's disease. 27–32.
8.
Avina‐Cervantes, Juan Gabriel, et al.. (2022). Attention Mechanisms Evaluated on Stenosis Detection using X-ray Angiography Images. 9. 62–75. 2 indexed citations
9.
Ruiz-Pinales, José, et al.. (2022). Automatic identification of misogynistic sentiments on social networks. 10–18. 2 indexed citations
10.
Avina‐Cervantes, Juan Gabriel, et al.. (2021). Transfer Learning for Humanoid Robot Appearance-Based Localization in a Visual Map. IEEE Access. 9. 6868–6877. 12 indexed citations
11.
Avina‐Cervantes, Juan Gabriel, et al.. (2021). Hybrid classical–quantum Convolutional Neural Network for stenosis detection in X-ray coronary angiography. Expert Systems with Applications. 189. 116112–116112. 51 indexed citations
12.
Avina‐Cervantes, Juan Gabriel, et al.. (2020). Transfer Learning for Stenosis Detection in X-ray Coronary Angiography. Mathematics. 8(9). 1510–1510. 39 indexed citations
13.
Ruiz-Pinales, José, et al.. (2020). Localización de referencias cefalométricas en radiografías laterales de cráneo: Una revisión sistemática. Research in computing science. 149. 339–352.
14.
Saha, Baidya Nath, et al.. (2020). Digital Diversions for Educational Recess: An Evaluation of Mood Reinforcements with Interactive Multimedia. Research in computing science. 119–134. 1 indexed citations
15.
Ruiz-Pinales, José, et al.. (2020). Multi-Stroke handwriting character recognition based on sEMG using convolutional-recurrent neural networks. Mathematical Biosciences & Engineering. 17(5). 5432–5448. 15 indexed citations
16.
Sánchez-Yáñez, Raúl E., et al.. (2015). Adaptive sigmoid function bihistogram equalization for image contrast enhancement. Journal of Electronic Imaging. 24(5). 53009–53009. 18 indexed citations
17.
Ledesma, Sergio, et al.. (2011). Hurst Parameter Estimation Using Artificial Neural Networks. Journal of Applied Research and Technology. 9(2). 9 indexed citations
18.
Ruiz-Pinales, José, et al.. (2008). CURSIVE WORD RECOGNITION BASED ON INTERACTIVE ACTIVATION AND EARLY VISUAL PROCESSING MODELS. International Journal of Neural Systems. 18(5). 419–431. 5 indexed citations
19.
Ruiz-Pinales, José, et al.. (2004). Cursive Word Recognition Using a Novel Feature Extraction Method and a Neural Network.. 479–484. 1 indexed citations
20.
Ruiz-Pinales, José & Éric Lecolinet. (2002). Cursive handwriting recognition using the Hough transform and a neural network. 2. 231–234. 11 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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2026