N. Barreira

975 citations
49 papers · 521 indexed · h-index 13

N. Barreira

48 papers receiving 500 citations

Peers

N. Barreira
Comparison fields: 5 of 63
  • Ophthalmology 332
  • Radiology, Nuclear Medicine and Imaging 359
  • Computer Vision and Pattern Recognition 135
  • Immunology and Allergy 37
  • Signal Processing 41
Replace A. Mosquera with:
A. Mosquera Spain
Jianyang Xie China
Siamak Yousefi United States
Francesco Girardi Italy
Hideharu Ohsugi Japan
Naofumi Ishitobi Japan
Pingbo Ouyang China
Juhani Pietilä Finland
Swamidoss Issac Niwas India
N. Barreira relative to A. Mosquera Spain A. Mosquera's profile →
Citations per field
00.5×10×13.7×
A. Mosquera · 1×
Citations per year

Countries citing papers authored by N. Barreira

Since Specialization
Citations

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

Fields of papers citing papers by N. Barreira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 20233
4 20181
5 201717
6
On the analysis of feature selection techniques in a conjunctival hyperemia grading framework.
20162
7 201611
8 201619
9 201613
10 20169
11 201612
12 20151
13 20133
14 201318
15 20138
16 20123
17 20112
18 201039
19 200964
20
Automated three stage red lesions detection in digital color fundus images
20089

About N. Barreira

N. Barreira is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 49 papers that have together received 521 indexed citations. Recurring topics across this work include Glaucoma and retinal disorders (26 papers), Retinal Imaging and Analysis (24 papers), Ocular Surface and Contact Lens (14 papers), Retinal Diseases and Treatments (9 papers), Optical Coherence Tomography Applications (5 papers), Medical Image Segmentation Techniques (4 papers), Image and Object Detection Techniques (4 papers) and Retinal and Optic Conditions (4 papers). The work is most often cited by research in Ophthalmology (332 citations), Radiology, Nuclear Medicine and Imaging (359 citations) and Computer Vision and Pattern Recognition (135 citations). N. Barreira has collaborated with scholars based in Spain, United Kingdom and Portugal. Frequent co-authors include Manuel G. Penedo, Marcos Ortega, José Rouco, Marı́a J. Carreira, Jorge Novo, A. Mosquera, Brais Cancela, Marc Sáez, Carlos García‐Resúa and Francisco Gómez‐Ulla. Their work appears in journals such as Pattern Recognition, Pattern Recognition Letters and Computer Methods and Programs in Biomedicine.

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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