Eduardo Fidalgo
- Artificial Intelligence top 5%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Enrique AlegreLaura Fernández-RoblesV́ıctor González-CastroRocío Aláiz-RodríguezFrancisco Jáñez-MartinoAkanksha JoshiDeisy ChavesGeorge Azzopardi
- Topics
- Spam and Phishing Detection (12 papers)Advanced Image and Video Retrieval Techniques (11 papers)Digital Media Forensic Detection (9 papers)
In The Last Decade
Eduardo Fidalgo
51 papers receiving 996 citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Artificial Intelligence 469
- Information Systems 345
- Computer Vision and Pattern Recognition 246
- Signal Processing 195
- Computer Networks and Communications 150
Countries citing papers authored by Eduardo Fidalgo
This map shows the geographic impact of Eduardo Fidalgo'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 Eduardo Fidalgo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eduardo Fidalgo more than expected).
Fields of papers citing papers by Eduardo Fidalgo
This network shows the impact of papers produced by Eduardo Fidalgo. 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 Eduardo Fidalgo. The network helps show where Eduardo Fidalgo may publish in the future.
Co-authorship network of co-authors of Eduardo Fidalgo
This figure shows the co-authorship network connecting the top 25 collaborators of Eduardo Fidalgo. A scholar is included among the top collaborators of Eduardo Fidalgo 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 Eduardo Fidalgo. Eduardo Fidalgo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 14 | |
| 6 | 9 | |
| 7 | 4 | |
| 8 | 12 | |
| 9 | 21 | |
| 10 | 20 | |
| 11 | 27 | |
| 12 | 53 | |
| 13 | 1 | |
| 14 | 9 | |
| 15 | 6 | |
| 16 | Assessment and Estimation of Face Detection Performance Based on Deep Learning for Forensic Applicationsbreakdown → | 241 |
| 17 | 4 | |
| 18 | 6 | |
| 19 | 11 | |
| 20 | 1 |
About Eduardo Fidalgo
Eduardo Fidalgo is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 56 papers that have together received 1.1k indexed citations. Recurring topics across this work include Spam and Phishing Detection (12 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Digital Media Forensic Detection (9 papers). The work is most often cited by research in Signal Processing (195 citations), Information Systems (345 citations) and Artificial Intelligence (469 citations). Eduardo Fidalgo has collaborated with scholars based in Spain, India and Mexico. Frequent co-authors include Enrique Alegre, Laura Fernández-Robles, V́ıctor González-Castro, Rocío Aláiz-Rodríguez, Francisco Jáñez-Martino, Akanksha Joshi, Deisy Chaves, George Azzopardi, Abhishek Gangwar and A. Gangwar. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.
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.