Jesús Salido

1.3k total citations · 1 hit paper
30 papers, 863 citations indexed

About

Jesús Salido is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Artificial Intelligence. According to data from OpenAlex, Jesús Salido has authored 30 papers receiving a total of 863 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 11 papers in Biophysics and 9 papers in Artificial Intelligence. Recurrent topics in Jesús Salido's work include Cell Image Analysis Techniques (11 papers), AI in cancer detection (6 papers) and Image Retrieval and Classification Techniques (5 papers). Jesús Salido is often cited by papers focused on Cell Image Analysis Techniques (11 papers), AI in cancer detection (6 papers) and Image Retrieval and Classification Techniques (5 papers). Jesús Salido collaborates with scholars based in Spain, United States and Mexico. Jesús Salido's co-authors include Gloria Bueno, Óscar Déniz, Fernando De la Torre, Jesús Ruiz-Santaquiteria, Gabriel Cristóbal, Marcial García‐Rojo, M. Milagro Fernández-Carrobles, Noelia Vállez, Saúl Blanco and Aníbal Pedraza and has published in prestigious journals such as PLoS ONE, Computers and Electronics in Agriculture and Pattern Recognition Letters.

In The Last Decade

Jesús Salido

28 papers receiving 832 citations

Hit Papers

Face recognition using Histograms of Oriented Gradients 2011 2026 2016 2021 2011 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jesús Salido Spain 13 477 166 116 112 100 30 863
Jui-Cheng Yen Taiwan 11 574 1.2× 202 1.2× 101 0.9× 40 0.4× 46 0.5× 27 1.0k
P. Kruizinga Netherlands 7 605 1.3× 152 0.9× 217 1.9× 43 0.4× 55 0.6× 17 927
Muhammad Jaleed Khan Pakistan 14 419 0.9× 259 1.6× 417 3.6× 46 0.4× 80 0.8× 36 1.2k
Zunlei Feng China 14 762 1.6× 281 1.7× 84 0.7× 23 0.2× 42 0.4× 83 1.3k
Xuejin Chen China 20 762 1.6× 168 1.0× 99 0.9× 60 0.5× 34 0.3× 90 1.3k
Ghazali Sulong Malaysia 19 972 2.0× 211 1.3× 321 2.8× 65 0.6× 93 0.9× 116 1.2k
Ping‐Sung Liao Taiwan 4 374 0.8× 98 0.6× 112 1.0× 49 0.4× 22 0.2× 8 732
Gang Cao China 19 980 2.1× 165 1.0× 308 2.7× 49 0.4× 51 0.5× 84 1.4k

Countries citing papers authored by Jesús Salido

Since Specialization
Citations

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

Fields of papers citing papers by Jesús Salido

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jesús Salido

This figure shows the co-authorship network connecting the top 25 collaborators of Jesús Salido. A scholar is included among the top collaborators of Jesús Salido 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 Jesús Salido. Jesús Salido 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.
Bueno, Gloria, et al.. (2025). Real-Time Edge Computing vs. GPU-Accelerated Pipelines for Low-Cost Microscopy Applications. Electronics. 14(5). 930–930.
2.
Bueno, Gloria, et al.. (2024). Microscopic image quality in few-shot GAN-generated cyanobacteria images and its impact on classification networks. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 7–7. 2 indexed citations
3.
Pedraza, Aníbal, et al.. (2024). GNCnn: A QuPath extension for glomerulosclerosis and glomerulonephritis characterization based on deep learning. Computational and Structural Biotechnology Journal. 27. 35–47.
4.
Salido, Jesús, Noelia Vállez, González-López Lucía, Óscar Déniz, & Gloria Bueno. (2023). Comparison of deep learning models for digital H&E staining from unpaired label-free multispectral microscopy images. Computer Methods and Programs in Biomedicine. 235. 107528–107528. 13 indexed citations
5.
Salido, Jesús, et al.. (2021). Automatic Handgun Detection with Deep Learning in Video Surveillance Images. Applied Sciences. 11(13). 6085–6085. 26 indexed citations
6.
Salido, Jesús, Noelia Vállez, Óscar Déniz, et al.. (2021). MicroHikari3D: an automated DIY digital microscopy platform with deep learning capabilities. Biomedical Optics Express. 12(11). 7223–7223. 10 indexed citations
7.
Salido, Jesús, Carlos Sánchez, Jesús Ruiz-Santaquiteria, et al.. (2020). A Low-Cost Automated Digital Microscopy Platform for Automatic Identification of Diatoms. Applied Sciences. 10(17). 6033–6033. 34 indexed citations
9.
Fernández-Carrobles, M. Milagro, Gloria Bueno, Óscar Déniz, et al.. (2015). A CAD System for the Acquisition and Classification of Breast TMA in Pathology.. PubMed. 210. 756–60. 6 indexed citations
10.
Déniz, Óscar, et al.. (2014). A Vision-Based Localization Algorithm for an Indoor Navigation App. 7. 7–12. 6 indexed citations
11.
Fernández-Carrobles, M. Milagro, et al.. (2014). Frequential versus spatial colour textons for breast TMA classification. Computerized Medical Imaging and Graphics. 42. 25–37. 11 indexed citations
12.
Fernández-Carrobles, M. Milagro, Irene Tadeo, Gloria Bueno, et al.. (2013). TMA Vessel Segmentation Based on Color and Morphological Features: Application to Angiogenesis Research. The Scientific World JOURNAL. 2013(1). 263190–263190. 12 indexed citations
13.
Bueno, Gloria, M. Milagro Fernández-Carrobles, Óscar Déniz, et al.. (2013). An entropy-based automated approach to prostate biopsy ROI segmentation. Diagnostic Pathology. 8(S1). 3 indexed citations
14.
Fernández-Carrobles, M. Milagro, Gloria Bueno, Óscar Déniz, Jesús Salido, & Marcial García‐Rojo. (2013). Automatic Handling of Tissue Microarray Cores in High-Dimensional Microscopy Images. IEEE Journal of Biomedical and Health Informatics. 18(3). 999–1007. 10 indexed citations
15.
Redondo, Rafael, Gloria Bueno, Rodrigo Nava, et al.. (2012). Autofocus evaluation for brightfield microscopy pathology. Journal of Biomedical Optics. 17(3). 36008–36008. 53 indexed citations
16.
Bueno, Gloria, R. González, Óscar Déniz, et al.. (2012). A parallel solution for high resolution histological image analysis. Computer Methods and Programs in Biomedicine. 108(1). 388–401. 15 indexed citations
17.
Bueno, Gloria, Marcial García‐Rojo, Óscar Déniz, et al.. (2012). Emerging Trends: Grid Technology in Pathology. Studies in health technology and informatics. 179. 218–29. 4 indexed citations
18.
Déniz, Óscar, Gloria Bueno, Jesús Salido, & Fernando De la Torre. (2011). Face recognition using Histograms of Oriented Gradients. Pattern Recognition Letters. 32(12). 1598–1603. 421 indexed citations breakdown →
19.
Bueno, Gloria, et al.. (2010). A geodesic deformable model for automatic segmentation of image sequences applied to radiation therapy. International Journal of Computer Assisted Radiology and Surgery. 6(3). 341–350. 7 indexed citations
20.
Déniz, Óscar, Gloria Bueno, Jesús Salido, & Fernando De la Torre. (2010). FACE RECOGNITION WITH HISTOGRAMS OF ORIENTED GRADIENTS. 339–344. 4 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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