Leo Ramos

26 papers receiving 310 citations

Peers

Leo Ramos
Comparison fields: 5 of 83
  • Safety, Risk, Reliability and Quality 60
  • Computer Vision and Pattern Recognition 101
  • Industrial and Manufacturing Engineering 32
  • Media Technology 24
  • Global and Planetary Change 39
Replace Edmundo Casas with:
Edmundo Casas Spain
Plamen Zahariev Bulgaria
Margarita N. Favorskaya Russia
Pei Guo China
George E. Sakr Lebanon
Emir Buza Bosnia and Herzegovina
Qiang Gao China
Damir Krstinić Croatia
Leo Ramos relative to Edmundo Casas Spain Edmundo Casas's profile →
Citations per field
00.5×1.5×2.4×
Edmundo Casas · 1×
Citations per year

Countries citing papers authored by Leo Ramos

Since Specialization
Citations

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

Fields of papers citing papers by Leo Ramos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Leo Ramos, 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 Leo Ramos Line = papers co-authored together Leo Ramos links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202373
2 202431
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9 202315
10 202512
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12 20257
13 20236
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About Leo Ramos

Leo Ramos is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality, Artificial Intelligence, Global and Planetary Change and Political Science and International Relations, having authored 32 papers that have together received 317 indexed citations. Recurring topics across this work include Fire Detection and Safety Systems (5 papers), Video Surveillance and Tracking Methods (4 papers), Artificial Intelligence in Law (3 papers), Advanced Neural Network Applications (3 papers), Remote-Sensing Image Classification (3 papers), Fire effects on ecosystems (3 papers), Infrastructure Maintenance and Monitoring (2 papers) and Image Enhancement Techniques (2 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (60 citations), Computer Vision and Pattern Recognition (101 citations), Industrial and Manufacturing Engineering (32 citations), Media Technology (24 citations) and Global and Planetary Change (39 citations). Leo Ramos has collaborated with scholars based in Ecuador, Spain and United States. Frequent co-authors include Francklin Rivas, Edmundo Casas, Eduardo Bendek, Ángel D. Sappa, Manuel Eugenio Morocho-Cayamcela, Oscar Chang, Juan Carlos Durán, Juan M. Santos-Gago, Cenk Temizel and J. Gallardo. Their work appears in journals such as IEEE Access, Multimedia Tools and Applications, Scientific Reports, Journal of Pipeline Science and Engineering and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

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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