Mauricio Villegas

1.5k citations
25 papers · 349 indexed · h-index 12
Topics
Handwritten Text Recognition Techniques (11 papers)Image Retrieval and Classification Techniques (9 papers)Image Processing and 3D Reconstruction (8 papers)

In The Last Decade

Mauricio Villegas

25 papers receiving 322 citations

Peers

Mauricio Villegas
Comparison fields: 5 of 50
  • Computer Vision and Pattern Recognition 318
  • Artificial Intelligence 108
  • Media Technology 67
  • Signal Processing 48
  • Information Systems 22
Replace Joan Puigcerver with:
Joan Puigcerver Spain
Wataru Ohyama Japan
R. Legault Canada
J. Gorbe-Moya Spain
Stanley Janet United States
Stefan Fiel Austria
C. Nadal Canada
Yaqiang Wu China
Philippe Mulhem France
Jayant Kumar United States
Mauricio Villegas relative to Joan Puigcerver Spain Joan Puigcerver's profile →
Citations per field
00.5×1.5×
Joan Puigcerver · 1×
Citations per year

Countries citing papers authored by Mauricio Villegas

Since Specialization
Citations

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

Fields of papers citing papers by Mauricio Villegas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mauricio Villegas

This figure shows the co-authorship network connecting the top 25 collaborators of Mauricio Villegas. A scholar is included among the top collaborators of Mauricio Villegas 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 Mauricio Villegas. Mauricio Villegas 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
#WorkIndexed citations
1 54
2 17
3 15
4 19
5 4
6 48
7 13
8 1
9 3
10
Overview of the ImageCLEF 2016 Handwritten Scanned Document Retrieval Task.
4
11 3
12 3
13
Overview of the ImageCLEF 2014 Scalable Concept Image Annotation Task
10
14 2
15
Overview of the ImageCLEF 2013 Scalable Concept Image Annotation Subtask
27
16 3
17 2
18 3
19 13
20 15

About Mauricio Villegas

Mauricio Villegas is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 25 papers that have together received 349 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (11 papers), Image Retrieval and Classification Techniques (9 papers) and Image Processing and 3D Reconstruction (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (318 citations), Media Technology (67 citations) and Signal Processing (48 citations). Mauricio Villegas has collaborated with scholars based in Spain, United Kingdom and Netherlands. Frequent co-authors include Roberto Paredes, Alícia Fornés, Enrique Vidal, Pau Riba, Joan Andreu Sánchez, Marçal Rusiñol, Alejandro H. Toselli, Lei Kang, Verónica Romero and Bart Thomée. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Pattern Recognition Letters.

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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