Manuel Ramos‐Cabrer

77 papers receiving 693 citations

Peers

Manuel Ramos‐Cabrer
Comparison fields: 5 of 74
  • Information Systems 458
  • Computer Vision and Pattern Recognition 302
  • Artificial Intelligence 209
  • Sociology and Political Science 200
  • Computer Networks and Communications 178
Replace Alberto Gil‐Solla with:
Alberto Gil‐Solla Spain
Yolanda Blanco‐Fernández Spain
Heung-Nam Kim Canada
José Palazzo Moreira de Oliveira Brazil
Mike Gartrell United States
Ilaria Torre Italy
Yetunde Folajimi United States
Chumki Basu United States
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Manuel Ramos‐Cabrer relative to Alberto Gil‐Solla Spain Alberto Gil‐Solla's profile →
Citations per field
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Alberto Gil‐Solla · 1×
Citations per year

Countries citing papers authored by Manuel Ramos‐Cabrer

Since Specialization
Citations

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

Fields of papers citing papers by Manuel Ramos‐Cabrer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Manuel Ramos‐Cabrer. 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 Manuel Ramos‐Cabrer. The network helps show where Manuel Ramos‐Cabrer may publish in the future.

Co-authorship network of co-authors of Manuel Ramos‐Cabrer

This figure shows the co-authorship network connecting the top 25 collaborators of Manuel Ramos‐Cabrer. A scholar is included among the top collaborators of Manuel Ramos‐Cabrer 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 Manuel Ramos‐Cabrer. Manuel Ramos‐Cabrer 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 6
2 10
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5 1
6 13
7 10
8 30
9 4
10 2
11 7
12 39
13 25
14 13
15 4
16 1
17 1
18 10
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A MHP Receiver over RT-Linux for Digital TV.
0
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Exploring T-Learning in the MHP Context.
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About Manuel Ramos‐Cabrer

Manuel Ramos‐Cabrer is a scholar working on Information Systems, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 81 papers that have together received 746 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (38 papers), Multimedia Communication and Technology (32 papers) and Video Analysis and Summarization (24 papers). The work is most often cited by research in Information Systems (458 citations), Computer Vision and Pattern Recognition (302 citations) and Computer Science Applications (56 citations). Manuel Ramos‐Cabrer has collaborated with scholars based in Spain, Ecuador and Portugal. Frequent co-authors include Alberto Gil‐Solla, José J. Pazos‐Arias, Martín López‐Nores, Yolanda Blanco‐Fernández, Ana Fernández Vilas, Rebeca P. Dı́az Redondo, Jorge García‐Duque, Jack F. Bravo‐Torres, Jorge Duque and Marta Rey-López. Their work appears in journals such as Expert Systems with Applications, Computers & Education and Sensors.

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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