Fernando Trinta

456 citations
60 papers · 282 · h-index 10

Impact in

Papers in

Fernando Trinta

49 papers receiving 271 citations

Peers

Fernando Trinta
Comparison fields: 5 of 46
  • Computer Networks and Communications 128
  • Computer Vision and Pattern Recognition 109
  • Human-Computer Interaction 27
  • Information Systems 103
  • Computer Science Applications 25
Replace Dejan Kovachev with:
Dejan Kovachev Germany
Guido Lemos de Souza Filho Brazil
Cristina Frà Italy
David S. Munro Australia
Nektarios Moumoutzis Greece
Leonel Merino Chile
Kuldeep Singh Yadav India
Weikai Xie China
Selim İckin Sweden
Weijia He United States
Fernando Trinta relative to Dejan Kovachev Germany Dejan Kovachev's profile →
Citations per field
00.5×4.1×
Dejan Kovachev · 1×
Citations per year

Countries citing papers authored by Fernando Trinta

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Trinta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201734
2 201624
3 201422
4 201515
5 202013
6 201913
7 201912
8 201811
9 20179
10 20159
11 20178
12 20167
13 20157
14 20176
15 20186
16 20176
17 20065
18 20185
19 20084
20 20144

About Fernando Trinta

Fernando Trinta is a scholar working on Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence, having authored 60 papers that have together received 282 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (26 papers), Context-Aware Activity Recognition Systems (17 papers), Cloud Computing and Resource Management (15 papers), Software System Performance and Reliability (6 papers), Green IT and Sustainability (6 papers), Service-Oriented Architecture and Web Services (5 papers), IoT Networks and Protocols (4 papers) and Caching and Content Delivery (4 papers). The work is most often cited by research in Computer Networks and Communications (128 citations), Computer Vision and Pattern Recognition (109 citations), Human-Computer Interaction (27 citations), Information Systems (103 citations) and Computer Science Applications (25 citations). Fernando Trinta has collaborated with scholars based in Brazil, United States and Portugal. Frequent co-authors include Windson Viana, Paulo A. L. Rêgo, José Neuman de Souza, Lincoln S. Rocha, Emanuel Ferreira Coutinho, Dário Vieira, Carlos Ferraz, Omar Andrés Carmona Cortes, Geber Ramalho and Emanuele Santos. Their work appears in journals such as Pervasive and Mobile Computing, Computer Communications, Sensors, Multimedia Tools and Applications and Computing.

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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