Débora Corrêa

483 total citations
38 papers, 298 citations indexed

About

Débora Corrêa is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Débora Corrêa has authored 38 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 16 papers in Signal Processing and 15 papers in Artificial Intelligence. Recurrent topics in Débora Corrêa's work include Music and Audio Processing (10 papers), Music Technology and Sound Studies (9 papers) and Complex Systems and Time Series Analysis (7 papers). Débora Corrêa is often cited by papers focused on Music and Audio Processing (10 papers), Music Technology and Sound Studies (9 papers) and Complex Systems and Time Series Analysis (7 papers). Débora Corrêa collaborates with scholars based in Australia, Brazil and Moldova. Débora Corrêa's co-authors include Francisco A. Rodrigues, Michael Small, David M. Walker, Luís Gustavo Nonato, Thomas Stemler, Alexandre L. M. Levada, Rodrigo Fernandes de Mello, John Duncan, Nelson D. A. Mascarenhas and Sally Thompson and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Environmental Research Letters.

In The Last Decade

Débora Corrêa

36 papers receiving 284 citations

Peers

Débora Corrêa
Comparison fields: 5 of 82
  • Signal Processing 104
  • Computer Vision and Pattern Recognition 101
  • Artificial Intelligence 78
  • Cognitive Neuroscience 54
  • Statistical and Nonlinear Physics 45
Replace M. Kim with:
M. Kim United States
Granville Tunnicliffe‐Wilson Ghana
Pierre-François Marteau France
Jiulong Zhang China
Namgil Lee South Korea
Pierce Lai United Kingdom
Chunhua Bian China
Sunitha Basodi United States
M. M. Gabr Egypt
F. Desobry France
M. Kim United States View profile →
Citations per field, relative to Débora Corrêa
Débora Corrêa · 1×
Citations per year, relative to Débora Corrêa
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Countries citing papers authored by Débora Corrêa

Since Specialization
Citations

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

Fields of papers citing papers by Débora Corrêa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Débora Corrêa

This figure shows the co-authorship network connecting the top 25 collaborators of Débora Corrêa. A scholar is included among the top collaborators of Débora Corrêa 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 Débora Corrêa. Débora Corrêa 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
# Work Indexed citations
1 1
2 0
3 1
4 39
5 8
6 5
7 5
8 0
9 24
10 10
11 3
12 4
13 7
14 2
15 11
16
Similarity graph: visual exploration of song collections
4
17 3
18
RBPCA MaxLike : A Novel Statistic Classifier for Face Recognition based on Block-Based PCA and Covariance Matrix Regularization
2
19 14
20 3

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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