Francisco R. Feito

1.8k total citations
109 papers, 1.3k citations indexed

About

Francisco R. Feito is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Geology. According to data from OpenAlex, Francisco R. Feito has authored 109 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Computer Graphics and Computer-Aided Design, 37 papers in Computer Vision and Pattern Recognition and 24 papers in Geology. Recurrent topics in Francisco R. Feito's work include Computational Geometry and Mesh Generation (37 papers), 3D Surveying and Cultural Heritage (24 papers) and Remote Sensing and LiDAR Applications (19 papers). Francisco R. Feito is often cited by papers focused on Computational Geometry and Mesh Generation (37 papers), 3D Surveying and Cultural Heritage (24 papers) and Remote Sensing and LiDAR Applications (19 papers). Francisco R. Feito collaborates with scholars based in Spain, Portugal and Netherlands. Francisco R. Feito's co-authors include Juan M. Jurado, Rafael J. Segura, Juan Carlos Torres, Carlos J. Ogáyar, Lidia Ortega, Antonio J. Rueda, Francisco Martínez, Juan J. Jiménez, A. García and Joaquim J. Sousa and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and Sensors.

In The Last Decade

Francisco R. Feito

107 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francisco R. Feito Spain 19 359 345 248 203 187 109 1.3k
Yongyang Xu China 24 45 0.1× 471 1.4× 752 3.0× 156 0.8× 195 1.0× 62 2.0k
Zhong Xie China 28 44 0.1× 568 1.6× 609 2.5× 428 2.1× 181 1.0× 116 2.7k
Jiawen Xu China 22 116 0.3× 171 0.5× 110 0.4× 258 1.3× 158 0.8× 123 2.2k
Roland Wahl Germany 6 131 0.4× 663 1.9× 828 3.3× 290 1.4× 1.0k 5.4× 6 1.7k
Maarten Vergauwen Belgium 22 188 0.5× 1.2k 3.3× 581 2.3× 102 0.5× 1.1k 5.8× 107 2.1k
Nicolas Paparoditis France 19 34 0.1× 467 1.4× 727 2.9× 86 0.4× 487 2.6× 76 1.4k
Daniel Filip United States 6 189 0.5× 287 0.8× 114 0.5× 219 1.1× 67 0.4× 8 780
Shuhan Shen China 19 58 0.2× 816 2.4× 360 1.5× 107 0.5× 436 2.3× 91 1.5k
Weimin Wang China 17 30 0.1× 329 1.0× 175 0.7× 54 0.3× 52 0.3× 81 1.1k

Countries citing papers authored by Francisco R. Feito

Since Specialization
Citations

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

Fields of papers citing papers by Francisco R. Feito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francisco R. Feito. 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 Francisco R. Feito. The network helps show where Francisco R. Feito may publish in the future.

Co-authorship network of co-authors of Francisco R. Feito

This figure shows the co-authorship network connecting the top 25 collaborators of Francisco R. Feito. A scholar is included among the top collaborators of Francisco R. Feito 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 Francisco R. Feito. Francisco R. Feito 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.
Ogáyar, Carlos J., et al.. (2024). Classification of Grapevine Varieties Using UAV Hyperspectral Imaging. Remote Sensing. 16(12). 2103–2103. 5 indexed citations
2.
Ogáyar, Carlos J., et al.. (2023). Efficient generation of occlusion-aware multispectral and thermographic point clouds. Computers and Electronics in Agriculture. 207. 107712–107712. 5 indexed citations
3.
Jurado, Juan M., et al.. (2022). 3D tools for building and infrastructures inspection from thermal UAS data: first steps. Procedia Structural Integrity. 42. 1121–1127. 1 indexed citations
4.
Ogáyar, Carlos J., et al.. (2022). Metaheuristics for the optimization of Terrestrial LiDAR set-up. Automation in Construction. 146. 104675–104675. 10 indexed citations
5.
Ogáyar, Carlos J., et al.. (2022). Modeling of the 3D Tree Skeleton Using Real-World Data: A Survey. IEEE Transactions on Visualization and Computer Graphics. 29(12). 4920–4935. 7 indexed citations
6.
Ogáyar, Carlos J., et al.. (2022). A GPU-Accelerated Framework for Simulating LiDAR Scanning. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–18. 14 indexed citations
7.
Jurado, Juan M., et al.. (2021). An efficient method for acquisition of spectral BRDFs in real-world scenarios. Computers & Graphics. 102. 154–163. 8 indexed citations
8.
Madeira, Joaquim, et al.. (2021). A virtual reality simulator for training the surgical reduction of patient-specific supracondylar humerus fractures. International Journal of Computer Assisted Radiology and Surgery. 17(1). 65–73. 12 indexed citations
9.
Jurado, Juan M., Luís Pádua, Jonáš Hruška, Francisco R. Feito, & Joaquim J. Sousa. (2021). An Efficient Method for Generating UAV-Based Hyperspectral Mosaics Using Push-Broom Sensors. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 6515–6531. 19 indexed citations
10.
Jurado, Juan M., et al.. (2020). Semantic Segmentation of Natural Materials on a Point Cloud Using Spatial and Multispectral Features. Sensors. 20(8). 2244–2244. 16 indexed citations
11.
Feito, Francisco R., et al.. (2020). Automatic detection of landmarks for the analysis of a reduction of supracondylar fractures of the humerus. Medical Image Analysis. 64. 101729–101729. 17 indexed citations
12.
Jurado, Juan M., Luís Pádua, Francisco R. Feito, & Joaquim J. Sousa. (2020). Automatic Grapevine Trunk Detection on UAV-Based Point Cloud. Remote Sensing. 12(18). 3043–3043. 44 indexed citations
13.
Feito, Francisco R., et al.. (2019). Automatic Detection of Distal Humerus Features: First Steps. 354–359. 1 indexed citations
14.
Rueda, Antonio J., et al.. (2018). A formal framework for the representation of stack-based terrains. International Journal of Geographical Information Systems. 32(10). 1999–2022. 4 indexed citations
15.
Ortega, Lidia, et al.. (2015). Design of Topologically Structured Geo-database for Interactive Navigation and Exploration in 3D Web-Based Urban Information Systems. Journal of Environmental Informatics. 19(2). 79–92. 5 indexed citations
16.
García, A., Juan Ruiz de Miras, & Francisco R. Feito. (2005). Algebraic Representation of CSG Solids Built from Free-Form Primitives. Digital Library (University of West Bohemia). 1–4. 1 indexed citations
17.
Segura, Rafael J., Francisco R. Feito, & Juan Ruiz de Miras. (2004). Non-evaluated manipulation of complex CSG solids. Digital Library (University of West Bohemia). 403–410. 1 indexed citations
18.
Jiménez, Juan J., Rafael J. Segura, & Francisco R. Feito. (2004). Efficient Collision Detection between 2D Polygons. Digital Library (University of West Bohemia). 191–198. 16 indexed citations
19.
Rueda, Antonio J., Rafael J. Segura, Francisco R. Feito, Juan Ruiz de Miras, & Carlos J. Ogáyar. (2004). Voxelization of solids using simplicial coverings. Digital Library (University of West Bohemia). 227–234. 4 indexed citations
20.
Segura, Rafael J. & Francisco R. Feito. (2001). Algorithms to Test Ray-Triangle Intersection. Comparative Study. Digital Library (University of West Bohemia). 76–81. 15 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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