Marta Mejail

1.1k citations
45 papers · 668 indexed · h-index 14

Marta Mejail

40 papers receiving 649 citations

Peers

Marta Mejail
Comparison fields: 5 of 94
  • Computer Vision and Pattern Recognition 341
  • Media Technology 121
  • Aerospace Engineering 317
  • Environmental Engineering 68
  • Geology 15
Replace Rudolf Mester with:
Rudolf Mester Germany
Sunita Hingorani United States
Kai Briechle Germany
Donggyu Sim South Korea
Yvan G. Leclerc United States
D. Keren Israel
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Zhe Chen China
F.C.A. Groen Netherlands
Marta Mejail relative to Rudolf Mester Germany Rudolf Mester's profile →
Citations per field
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Citations per year

Countries citing papers authored by Marta Mejail

Since Specialization
Citations

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

Fields of papers citing papers by Marta Mejail

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20217
3 201713
4 20169
5 201532
6 201325
7 201023
8
SAR Image Segmentation using a Fast Level Set Technique
20082
9 20082
10 20071
11 20071
12 200619
13 20052
14 200356
15
SAR image segmentation using B-Spline deformable contours
20020
16
Approximation of distributions for SAR images: proposal, evaluation and practical consequences
200130
17
Parametric roughness estimation in amplitude SAR images under the multiplicative model
200015
18
Models for Synthetic Aperture Radar Image Analysis
199913
19 19981
20 19981

About Marta Mejail

Marta Mejail is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Aerospace Engineering, having authored 45 papers that have together received 668 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (11 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (11 papers), Advanced Image and Video Retrieval Techniques (7 papers), Robotics and Sensor-Based Localization (7 papers), Image and Object Detection Techniques (6 papers), Advanced Vision and Imaging (6 papers), Remote-Sensing Image Classification (5 papers) and Face and Expression Recognition (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (341 citations), Media Technology (121 citations) and Aerospace Engineering (317 citations). Marta Mejail has collaborated with scholars based in Argentina, Brazil and Spain. Frequent co-authors include Julio Jacobo-Berlles, Alejandro C. Frery, Matías Nitsche, Tomáš Krajník, Libor Přeučil, Luis Gómez, Tom Duckett, Jan Faigl, Oscar H. Bustos and Petr Vaněk.

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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