María Pérez‐Ortiz

2.8k citations
59 papers · 1.6k indexed · 3 hit papers · h-index 19

María Pérez‐Ortiz

56 papers receiving 1.5k citations

Hit Papers

Artificial Int...73201520262018202250100150200250

Peers

María Pérez‐Ortiz
Comparison fields: 5 of 148
  • Health Informatics 31
  • Artificial Intelligence 450
  • Computer Science Applications 72
  • Computer Vision and Pattern Recognition 241
  • Environmental Engineering 143
Replace Rashedur M. Rahman with:
Rashedur M. Rahman Bangladesh
François Petitjean Australia
Muhammad Aslam Pakistan
Sheifali Gupta India
Tomás F. Pena Spain
Ribana Roscher Germany
Jyotir Moy Chatterjee India
Michel Lang Germany
Asdrúbal López‐Chau Mexico
Uzair Aslam Bhatti China
María Pérez‐Ortiz relative to Rashedur M. Rahman Bangladesh Rashedur M. Rahman's profile →
Citations per field
00.5×1.5×2.1×
Rashedur M. Rahman · 1×
Citations per year

Countries citing papers authored by María Pérez‐Ortiz

Since Specialization
Citations

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

Fields of papers citing papers by María Pérez‐Ortiz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by María Pérez‐Ortiz. 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 María Pérez‐Ortiz. The network helps show where María Pérez‐Ortiz may publish in the future.

Co-authorship network

The 25 scholars most cited alongside María Pérez‐Ortiz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with María Pérez‐Ortiz Line = papers co-authored together María Pérez‐Ortiz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20240
3
Artificial Intelligence Alone Will Not Democratise Education: On Educational Inequality, Techno-Solutionism and Inclusive Toolsbreakdown →
202473
4 20241
5 202354
6 202210
7
Seasonal Arctic sea ice forecasting with probabilistic deep learningbreakdown →
2021158
8 20203
9 201946
10
ORCA: A Matlab/Octave Toolbox for Ordinal Regression
201911
11 20182
12 201738
13 201762
14 20164
15 20163
16 201634
17
Ordinal Regression Methods: Survey and Experimental Studybreakdown →
2015281
18 2015161
19 201445
20
Multi-scale Support Vector Machine Optimization by Kernel Target-Alignment.
20131

About María Pérez‐Ortiz

María Pérez‐Ortiz is a scholar working on Computer Science Applications, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 59 papers that have together received 1.6k indexed citations. Recurring topics across this work include Face and Expression Recognition (9 papers), Online Learning and Analytics (7 papers), Imbalanced Data Classification Techniques (7 papers), Text and Document Classification Technologies (7 papers), Smart Agriculture and AI (6 papers), Machine Learning and Data Classification (6 papers), Remote Sensing in Agriculture (5 papers) and Neural Networks and Applications (5 papers). The work is most often cited by research in Health Informatics (31 citations), Artificial Intelligence (450 citations) and Computer Science Applications (72 citations). María Pérez‐Ortiz has collaborated with scholars based in United Kingdom, Spain and United States. Frequent co-authors include César Hervás‐Martínez, Pedro Antonio Gutiérrez, José M. Peña, Javier Sánchez‐Monedero, Francisco Fernández‐Navarro, Francisca López Granados, Jorge Torres‐Sánchez, John Shawe‐Taylor, Rafał Mantiuk and Sancho Salcedo‐Sanz. Their work appears in journals such as Nature Communications, Scientific Reports and IEEE Transactions on Image Processing.

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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