N. Pavón

1.2k citations
44 papers · 894 · h-index 16

Impact in

Papers in

N. Pavón

41 papers receiving 881 citations

Peers

N. Pavón
Comparison fields: 5 of 105
  • Radiation 324
  • Radiology, Nuclear Medicine and Imaging 316
  • Computer Vision and Pattern Recognition 176
  • Nuclear and High Energy Physics 93
  • Plant Science 168
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Chao Lu China
Ahmed S. Salama Egypt
Harbinder Singh India
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M. Gorgoń Poland
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N. Pavón relative to Chao Lu China Chao Lu's profile →
Citations per field
00.5×10×20×30×40×46.5×
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Citations per year

Countries citing papers authored by N. Pavón

Since Specialization
Citations

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

Fields of papers citing papers by N. Pavón

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside N. Pavón, 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 N. Pavón Line = papers co-authored together N. Pavón links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005103
2 2015101
3 201690
4 201982
5 201559
6 200453
7 201746
8 200644
9 200637
10 200432
11 200622
12 200419
13 202018
14 200218
15 200416
16 202115
17 201415
18 200411
19 200511
20 201411

About N. Pavón

N. Pavón is a scholar working on Radiation, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Nuclear and High Energy Physics and Plant Science, having authored 44 papers that have together received 894 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (19 papers), Radiation Detection and Scintillator Technologies (19 papers), Particle Detector Development and Performance (9 papers), Smart Agriculture and AI (6 papers), Robotics and Automated Systems (4 papers), IoT and Edge/Fog Computing (4 papers), Advanced Radiotherapy Techniques (3 papers) and Context-Aware Activity Recognition Systems (3 papers). The work is most often cited by research in Radiation (324 citations), Radiology, Nuclear Medicine and Imaging (316 citations), Computer Vision and Pattern Recognition (176 citations), Nuclear and High Energy Physics (93 citations) and Plant Science (168 citations). N. Pavón has collaborated with scholars based in Spain, Portugal and Colombia. Frequent co-authors include J. Ferruz, Juan Antonio López, Miguel Á. Vega-Rodríguez, J. Benlloch, Á. Sebastiá, F. Sánchez, Christoph Lerche, Jorge D. Martínez, Roque Torres-Sánchez and F. Soto. Their work appears in journals such as Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, IEEE Transactions on Nuclear Science, Medical Physics, Sensors and Agricultural Water Management.

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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