Pablo Morales-Álvarez

492 total citations
25 papers, 321 citations indexed

About

Pablo Morales-Álvarez is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Pablo Morales-Álvarez has authored 25 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Signal Processing. Recurrent topics in Pablo Morales-Álvarez's work include AI in cancer detection (10 papers), Gaussian Processes and Bayesian Inference (9 papers) and Machine Learning and Data Classification (5 papers). Pablo Morales-Álvarez is often cited by papers focused on AI in cancer detection (10 papers), Gaussian Processes and Bayesian Inference (9 papers) and Machine Learning and Data Classification (5 papers). Pablo Morales-Álvarez collaborates with scholars based in Spain, United States and United Kingdom. Pablo Morales-Álvarez's co-authors include Rafael Molina, José Gutiérrez Fernández, M.A. González, Guillermo Quindós, Aggelos K. Katsaggelos, Pablo Ruiz, Gustau Camps‐Valls, Adrián Pérez-Suay, Lee Cooper and Ana B. Ruescas and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Geoscience and Remote Sensing and Expert Systems with Applications.

In The Last Decade

Pablo Morales-Álvarez

22 papers receiving 314 citations

Peers

Pablo Morales-Álvarez
Comparison fields: 5 of 93
  • Artificial Intelligence 141
  • Infectious Diseases 87
  • Epidemiology 66
  • Computer Vision and Pattern Recognition 56
  • Computer Science Applications 33
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Alexandre Lacoste Canada
Zhihao Peng China
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Matthias Chung United States
Liang Xiao China
Xudong Guo China
Auwalu Saleh Mubarak Cyprus
Amit Jain India
Qazi Mudassar Ilyas Saudi Arabia
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Citations per field, relative to Pablo Morales-Álvarez
Pablo Morales-Álvarez · 1×
Citations per year, relative to Pablo Morales-Álvarez
Pablo Morales-Álvarez · 1×

Countries citing papers authored by Pablo Morales-Álvarez

Since Specialization
Citations

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

Fields of papers citing papers by Pablo Morales-Álvarez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pablo Morales-Álvarez. 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 Pablo Morales-Álvarez. The network helps show where Pablo Morales-Álvarez may publish in the future.

Co-authorship network of co-authors of Pablo Morales-Álvarez

This figure shows the co-authorship network connecting the top 25 collaborators of Pablo Morales-Álvarez. A scholar is included among the top collaborators of Pablo Morales-Álvarez 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 Pablo Morales-Álvarez. Pablo Morales-Álvarez 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
# Work Indexed citations
1 0
2 5
3 5
4 0
5 2
6 0
7 5
8 5
9 10
10 11
11
Activation-level uncertainty in deep neural networks
2
12 22
13 27
14 18
15 28
16 4
17 12
18 2
19 2
20 99

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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