Moises Díaz

3.6k total citations · 1 hit paper
87 papers, 2.4k citations indexed

About

Moises Díaz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction. According to data from OpenAlex, Moises Díaz has authored 87 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Computer Vision and Pattern Recognition, 25 papers in Artificial Intelligence and 15 papers in Human-Computer Interaction. Recurrent topics in Moises Díaz's work include Handwritten Text Recognition Techniques (50 papers), Image Processing and 3D Reconstruction (21 papers) and Natural Language Processing Techniques (20 papers). Moises Díaz is often cited by papers focused on Handwritten Text Recognition Techniques (50 papers), Image Processing and 3D Reconstruction (21 papers) and Natural Language Processing Techniques (20 papers). Moises Díaz collaborates with scholars based in Spain, Italy and Canada. Moises Díaz's co-authors include Miguel A. Ferrer, Aythami Morales, Réjean Plamondon, Donato Impedovo, Giuseppe Pirlo, Antonio Castrillo, Pietro Cerri, Cynthia Hong, Peter Tontonoz and Andreas Fischer and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and Immunity.

In The Last Decade

Moises Díaz

75 papers receiving 2.3k citations

Hit Papers

Apoptotic Cells Promote Their Own Clearance and Immune To... 2009 2026 2014 2020 2009 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Moises Díaz Spain 23 1.1k 606 411 345 285 87 2.4k
H. Inoue Japan 36 1.3k 1.2× 77 0.1× 386 0.9× 70 0.2× 273 1.0× 241 4.9k
Shunji Mori Japan 15 1.4k 1.3× 75 0.1× 264 0.6× 292 0.8× 209 0.7× 102 2.4k
Sudipta Roy India 31 632 0.6× 97 0.2× 572 1.4× 111 0.3× 349 1.2× 147 2.7k
Narendra D. Londhe India 25 256 0.2× 197 0.3× 438 1.1× 41 0.1× 42 0.1× 125 1.9k
Bo‐Hao Chen Taiwan 27 1.3k 1.2× 110 0.2× 123 0.3× 669 1.9× 120 0.4× 120 2.1k
Yang Long China 22 618 0.6× 495 0.8× 611 1.5× 41 0.1× 242 0.8× 97 1.7k
Jian Lian China 20 313 0.3× 112 0.2× 221 0.5× 82 0.2× 458 1.6× 89 2.1k
S. Mori Japan 15 944 0.9× 100 0.2× 169 0.4× 217 0.6× 85 0.3× 39 1.4k
Harry Wechsler United States 24 454 0.4× 56 0.1× 328 0.8× 78 0.2× 119 0.4× 50 1.8k
Feng Lin Singapore 25 602 0.5× 67 0.1× 176 0.4× 131 0.4× 317 1.1× 142 2.0k

Countries citing papers authored by Moises Díaz

Since Specialization
Citations

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

Fields of papers citing papers by Moises Díaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Moises Díaz. 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 Moises Díaz. The network helps show where Moises Díaz may publish in the future.

Co-authorship network of co-authors of Moises Díaz

This figure shows the co-authorship network connecting the top 25 collaborators of Moises Díaz. A scholar is included among the top collaborators of Moises Díaz 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 Moises Díaz. Moises Díaz 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.
Díaz, Moises, et al.. (2025). Online Signature Verification based on the Lagrange formulation with 2D and 3D robotic models. Pattern Recognition. 164. 111581–111581. 1 indexed citations
2.
Gómez‐Sánchez, Leticia, et al.. (2025). Evolution of arterial stiffness and association with cardiovascular risk factors in the Spanish population. Follow-up to the study EVA. Medicina Clínica (English Edition). 164(9). 461–469.
3.
Gasmi, Mohamed, et al.. (2025). Enhancing breast cancer histopathological image classification: The impact of stain normalization on multilevel feature extraction. Biomedical Signal Processing and Control. 106. 107700–107700.
4.
Díaz, Moises, et al.. (2025). Integrating robotic kinematics and dynamics with online handwriting features for dysgraphia classification. Biomedical Signal Processing and Control. 112. 108560–108560.
6.
Mekyska, Jiří, Tomáš Urbánek, Vojtěch Zvončák, et al.. (2024). Graphomotor and Handwriting Disabilities Rating Scale (GHDRS): towards complex and objective assessment. arXiv (Cornell University). 29(1). 1–34. 1 indexed citations
7.
Domínguez‐Luis, María Jesús, Javier Castro‐Hernández, Ana Díaz‐Martín, et al.. (2024). Modulation of the K/BxN arthritis mouse model and the effector functions of human fibroblast‐like synoviocytes by liver X receptors. European Journal of Immunology. 54(11). e2451136–e2451136.
9.
Díaz, Moises, et al.. (2023). CowScreeningDB: A public benchmark database for lameness detection in dairy cows. Computers and Electronics in Agriculture. 216. 108500–108500. 4 indexed citations
10.
Ferrer, Miguel A., Moises Díaz, Cristina Carmona-Duarte, José J. Quintana, & Réjean Plamondon. (2023). Synthesis of 3D on-air signatures with the Sigma–Lognormal model. Knowledge-Based Systems. 265. 110365–110365. 5 indexed citations
11.
Faúndez-Zanuy, Marcos, Moises Díaz, & Miguel A. Ferrer. (2023). Online Signature Recognition: A Biologically Inspired Feature Vector Splitting Approach. Cognitive Computation. 16(1). 265–277. 6 indexed citations
12.
Chinarro, David, et al.. (2020). Comparison of Growth Patterns of COVID-19 Cases through the ARIMA and Gompertz Models. Case Studies: Austria, Switzerland, and Israel. SHILAP Revista de lepidopterología. 11(3). e0022–e0022. 8 indexed citations
13.
Ferrer, Miguel A., Moises Díaz, Cristina Carmona-Duarte, & Réjean Plamondon. (2019). Generating Off-line and On-line Forgeries from On-line Genuine Signatures. Acceda (Universidad de Las Palmas de Gran Canaria). 1–6. 6 indexed citations
14.
Ferrer, Miguel A., Moises Díaz, Cristina Carmona-Duarte, & Réjean Plamondon. (2018). A Biometric Attack Case Based on Signature Synthesis. Acceda (Universidad de Las Palmas de Gran Canaria). 1–6. 5 indexed citations
15.
Carmona-Duarte, Cristina, Rafael Torres‐Peralta, Moises Díaz, Miguel A. Ferrer, & Marcos Martín-Rincón. (2017). Myoelectronic signal-based methodology for the analysis of handwritten signatures. Human Movement Science. 55. 18–30. 7 indexed citations
16.
Díaz, Moises, Miguel A. Ferrer, & Robert Sabourin. (2016). Approaching the intra-class variability in multi-script static signature evaluation. Acceda (Universidad de Las Palmas de Gran Canaria). 1147–1152. 15 indexed citations
17.
Ito, Ayaka, Cynthia Hong, Kazuhiro Oka, et al.. (2016). Cholesterol Accumulation in CD11c+ Immune Cells Is a Causal and Targetable Factor in Autoimmune Disease. Immunity. 45(6). 1311–1326. 96 indexed citations
18.
Díaz, Moises, Miguel A. Ferrer, & Aythami Morales. (2015). Modeling the Lexical Morphology of Western Handwritten Signatures. PLoS ONE. 10(4). e0123254–e0123254. 19 indexed citations
19.
Morales, Aythami, et al.. (2014). The use of hyperspectral analysis for ink identification in handwritten documents. Acceda (Universidad de Las Palmas de Gran Canaria). 1–5. 15 indexed citations
20.
A-González, Noelia, Steven J. Bensinger, Cynthia Hong, et al.. (2009). Apoptotic Cells Promote Their Own Clearance and Immune Tolerance through Activation of the Nuclear Receptor LXR. Immunity. 31(2). 245–258. 544 indexed citations breakdown →

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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