Pablo Mesejo

1.9k total citations
39 papers, 943 citations indexed

About

Pablo Mesejo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Archeology. According to data from OpenAlex, Pablo Mesejo has authored 39 papers receiving a total of 943 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 12 papers in Archeology. Recurrent topics in Pablo Mesejo's work include Forensic Anthropology and Bioarchaeology Studies (12 papers), Dental Radiography and Imaging (8 papers) and Advanced Image and Video Retrieval Techniques (6 papers). Pablo Mesejo is often cited by papers focused on Forensic Anthropology and Bioarchaeology Studies (12 papers), Dental Radiography and Imaging (8 papers) and Advanced Image and Video Retrieval Techniques (6 papers). Pablo Mesejo collaborates with scholars based in Spain, France and Italy. Pablo Mesejo's co-authors include Radu Horaud, Stéphane Lathuilière, Xavier Alameda-Pineda, Óscar Ibáñez, Stefano Cagnoni, Óscar Cordón, Andrea Valsecchi, Daniel Pizarro, Sylvain Béorchia and Armand Abergel and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Expert Systems with Applications.

In The Last Decade

Pablo Mesejo

36 papers receiving 916 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pablo Mesejo Spain 16 289 274 168 102 97 39 943
Simone Palazzo Italy 16 202 0.7× 535 2.0× 152 0.9× 18 0.2× 162 1.7× 79 1.3k
Sansanee Auephanwiriyakul Thailand 16 445 1.5× 351 1.3× 132 0.8× 9 0.1× 41 0.4× 103 1.1k
Benoît Macq Belgium 21 180 0.6× 1.5k 5.4× 194 1.2× 23 0.2× 16 0.2× 111 2.2k
Miao Liao China 25 184 0.6× 908 3.3× 244 1.5× 54 0.5× 19 0.2× 102 1.6k
Shunji Mori Japan 15 264 0.9× 1.4k 5.1× 116 0.7× 72 0.7× 11 0.1× 102 2.4k
Aparecido Nilceu Marana Brazil 15 395 1.4× 640 2.3× 20 0.1× 12 0.1× 48 0.5× 58 1.0k
Mingyu Kim South Korea 10 670 2.3× 790 2.9× 58 0.3× 6 0.1× 39 0.4× 43 1.7k
Kari Saarinen Finland 9 156 0.5× 659 2.4× 118 0.7× 19 0.2× 13 0.1× 38 1.3k
Khurram Khurshid Pakistan 18 450 1.6× 950 3.5× 242 1.4× 11 0.1× 80 0.8× 87 2.0k

Countries citing papers authored by Pablo Mesejo

Since Specialization
Citations

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

Fields of papers citing papers by Pablo Mesejo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pablo Mesejo

This figure shows the co-authorship network connecting the top 25 collaborators of Pablo Mesejo. A scholar is included among the top collaborators of Pablo Mesejo 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 Mesejo. Pablo Mesejo 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.
2.
Mesejo, Pablo, et al.. (2024). A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making. ACM Computing Surveys. 56(11). 1–36. 3 indexed citations
3.
Valsecchi, Andrea, et al.. (2024). Information fusion for infant age estimation from deciduous teeth using machine learning. American Journal of Biological Anthropology. 184(2). e24912–e24912. 2 indexed citations
4.
Garcia, Manuel B., et al.. (2024). The level of strength of an explanation: A quantitative evaluation technique for post-hoc XAI methods. Pattern Recognition. 161. 111221–111221. 2 indexed citations
5.
Giráldez-Cru, Jesús, et al.. (2024). Unveiling Agents’ Confidence in Opinion Dynamics Models via Graph Neural Networks. IEEE Transactions on Computational Social Systems. 12(2). 725–737.
6.
Al-Sahaf, Harith, Pablo Mesejo, Ying Bi, & Mengjie Zhang. (2023). Evolutionary deep learning for computer vision and image processing. Applied Soft Computing. 151. 111159–111159. 6 indexed citations
7.
Lei, Bo, et al.. (2023). Exploring the trade-off between performance and annotation complexity in semantic segmentation. Engineering Applications of Artificial Intelligence. 123. 106299–106299. 6 indexed citations
8.
Gómez, Óscar, Pablo Mesejo, Óscar Ibáñez, et al.. (2023). Evaluating artificial intelligence for comparative radiography. International Journal of Legal Medicine. 138(1). 307–327. 4 indexed citations
9.
Bi, Ying, Bing Xue, Pablo Mesejo, Stefano Cagnoni, & Mengjie Zhang. (2022). A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future Trends. IEEE Transactions on Evolutionary Computation. 27(1). 5–25. 53 indexed citations
10.
Gómez, Óscar, Pablo Mesejo, & Óscar Ibáñez. (2021). Automatic segmentation of skeletal structures in X-ray images using deep learning for comparative radiography. Forensic Imaging. 26. 200458–200458. 3 indexed citations
11.
Bermejo, Enrique, Kei Taniguchi, Yoshinori Ogawa, et al.. (2021). Automatic landmark annotation in 3D surface scans of skulls: Methodological proposal and reliability study. Computer Methods and Programs in Biomedicine. 210. 106380–106380. 27 indexed citations
12.
Irurita, Javier, et al.. (2021). Analysis of the performance of machine learning and deep learning methods for sex estimation of infant individuals from the analysis of 2D images of the ilium. International Journal of Legal Medicine. 135(6). 2659–2666. 16 indexed citations
13.
Lathuilière, Stéphane, Pablo Mesejo, Xavier Alameda-Pineda, & Radu Horaud. (2020). A Comprehensive Analysis of Deep Regression. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(9). 2065–2081. 192 indexed citations
14.
Mesejo, Pablo, et al.. (2020). A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification. Applied Sciences. 10(14). 4703–4703. 37 indexed citations
15.
Valsecchi, Andrea, Javier Irurita, & Pablo Mesejo. (2019). Age estimation in forensic anthropology: methodological considerations about the validation studies of prediction models. International Journal of Legal Medicine. 133(6). 1915–1924. 19 indexed citations
16.
Lathuilière, Stéphane, et al.. (2018). Neural network based reinforcement learning for audio–visual gaze control in human–robot interaction. Pattern Recognition Letters. 118. 61–71. 35 indexed citations
17.
Mesejo, Pablo, Andrea Valsecchi, Linda Marrakchi‐Kacem, Stefano Cagnoni, & Sergio Damas. (2014). Biomedical image segmentation using geometric deformable models and metaheuristics. Computerized Medical Imaging and Graphics. 43. 167–178. 43 indexed citations
18.
Mesejo, Pablo, Samantha Zongaro, Barbara Bardoni, et al.. (2013). Visual Search of Neuropil-Enriched RNAs from Brain In Situ Hybridization Data through the Image Analysis Pipeline Hippo-ATESC. PLoS ONE. 8(9). e74481–e74481. 8 indexed citations
19.
20.
Porto-Pazos, Ana B., Pablo Mesejo, Marta Navarrete, et al.. (2011). Artificial Astrocytes Improve Neural Network Performance. PLoS ONE. 6(4). e19109–e19109. 52 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Simone Palazzo Breakdown of academic impact, for papers by Sansanee Auephanwiriyakul Breakdown of academic impact, for papers by Benoît Macq Breakdown of academic impact, for papers by Miao Liao Breakdown of academic impact, for papers by Shunji Mori Breakdown of academic impact, for papers by Aparecido Nilceu Marana Breakdown of academic impact, for papers by Mingyu Kim Breakdown of academic impact, for papers by Kari Saarinen Breakdown of academic impact, for papers by Khurram Khurshid
Rankless by CCL
2026