Ana F. Sequeira

834 citations
34 papers · 426 indexed · h-index 11

Ana F. Sequeira

30 papers receiving 419 citations

Peers

Ana F. Sequeira
Comparison fields: 5 of 70
  • Signal Processing 253
  • Computer Vision and Pattern Recognition 222
  • Catalysis 38
  • Safety Research 44
  • Information Systems 78
Replace Martin Drahanský with:
Martin Drahanský Czechia
Zhaofeng He China
Christof Kauba Austria
Kiran B. Raja Norway
Sunpreet S. Arora United States
Shejin Thavalengal Ireland
Heinz Hofbauer Austria
Ricardo Santos Portugal
Prathyusha Kanakam India
Hyeon Chang Lee South Korea
Ana F. Sequeira relative to Martin Drahanský Czechia Martin Drahanský's profile →
Citations per field
00.5×2.8×
Martin Drahanský · 1×
Citations per year

Countries citing papers authored by Ana F. Sequeira

Since Specialization
Citations

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

Fields of papers citing papers by Ana F. Sequeira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ana F. Sequeira. 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 Ana F. Sequeira. The network helps show where Ana F. Sequeira may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
2 20234
3 20237
4 20232
5 20227
6 202218
7 202223
8 20218
9 202127
10 20210
11
A robust fingerprint presentation attack detection method against unseen attacks through adversarial learning
20206
12 20208
13
Adversarial learning for a robust iris presentation attack detection method against unseen attack presentations
20196
14 201815
15 20183
16 201726
17 201618
18 201521
19 201427
20 201410

About Ana F. Sequeira

Ana F. Sequeira is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Safety Research, having authored 34 papers that have together received 426 indexed citations. Recurring topics across this work include Biometric Identification and Security (24 papers), Face recognition and analysis (16 papers), Face and Expression Recognition (7 papers), User Authentication and Security Systems (6 papers), Forensic and Genetic Research (5 papers), Forensic Fingerprint Detection Methods (4 papers), Digital Media Forensic Detection (4 papers) and Video Surveillance and Tracking Methods (2 papers). The work is most often cited by research in Signal Processing (253 citations), Computer Vision and Pattern Recognition (222 citations) and Catalysis (38 citations). Ana F. Sequeira has collaborated with scholars based in Portugal, Germany and United Kingdom. Frequent co-authors include Jaime S. Cardoso, Hélder P. Oliveira, Pedro C. Neto, Ana Rebelo, Naser Damer, James Ferryman, João Ribeiro Pinto, Fadi Boutros, Nuno M. T. Lourenço and Susana Barreiros. Their work appears in journals such as IEEE Access, Sensors, Green Chemistry, Information Fusion and IEEE Transactions on Biometrics Behavior and Identity Science.

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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