Eduardo M. Pereira
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 2%
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Machine Learning in Healthcare
- Anomaly Detection Techniques and Applications
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
Papers in
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- Human Pose and Action Recognition 6
- Video Surveillance and Tracking Methods 5
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- Anomaly Detection Techniques and Applications 5
- Adversarial Robustness in Machine Learning 1
- Machine Learning and Data Classification 1
- Co-authors
- Jaime S. Cardoso (6 shared papers)Ricardo Morla (2 shared papers)Adérito Seixas (1 shared paper)João Paulo Vilas‐Boas (1 shared paper)Ricardo Vardasca (1 shared paper)Álvaro A. Orozco (1 shared paper)G. Castellanos-Domínguez (1 shared paper)Andrés Marino Álvarez-Meza (1 shared paper)
In The Last Decade
Eduardo M. Pereira
11 papers receiving 1.2k citations
Eduardo M. Pereira's Hit Papers
Peers
Comparison fields: 5 of 151
- Health Informatics 103
- Artificial Intelligence 714
- Safety Research 80
- Health Information Management 33
- Information Systems and Management 42
Countries citing papers authored by Eduardo M. Pereira
This map shows the geographic impact of Eduardo M. Pereira'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 M. Pereira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eduardo M. Pereira more than expected).
Fields of papers citing papers by Eduardo M. Pereira
This network shows the impact of papers produced by Eduardo M. Pereira. 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 M. Pereira. The network helps show where Eduardo M. Pereira may publish in the future.
Co-authors
The 16 scholars most cited alongside Eduardo M. Pereira, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Machine Learning Interpretability: A Survey on Methods and Metrics Hit paper breakdown → | 2019 | 1176 |
| 2 | 2019 | 7 | |
| 3 | 2016 | 6 | |
| 4 | 2015 | 4 | |
| 5 | 2014 | 4 | |
| 6 | 2016 | 4 | |
| 7 | 2016 | 3 | |
| 8 | 2013 | 3 | |
| 9 | 2020 | 2 | |
| 10 | 2017 | 1 | |
| 11 | 2016 | 1 |
About Eduardo M. Pereira
Eduardo M. Pereira is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Social Psychology and Complementary and Manual Therapy, having authored 11 papers that have together received 1.2k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (6 papers), Anomaly Detection Techniques and Applications (5 papers), Video Surveillance and Tracking Methods (5 papers), Hand Gesture Recognition Systems (1 paper), Adversarial Robustness in Machine Learning (1 paper), Human Motion and Animation (1 paper), Evacuation and Crowd Dynamics (1 paper) and Machine Learning and Data Classification (1 paper). The work is most often cited by research in Health Informatics (103 citations), Artificial Intelligence (714 citations), Safety Research (80 citations), Health Information Management (33 citations) and Information Systems and Management (42 citations). Eduardo M. Pereira has collaborated with scholars based in Portugal, Colombia and Japan. Frequent co-authors include Jaime S. Cardoso, Ricardo Morla, Adérito Seixas, João Paulo Vilas‐Boas, Ricardo Vardasca, Álvaro A. Orozco, G. Castellanos-Domínguez, Andrés Marino Álvarez-Meza, Luciana de Rezende Pinto and Shin’ichi Satoh. Their work appears in journals such as Neural Computing and Applications, Journal of Visual Communication and Image Representation, The Visual Computer, The International Journal of Prosthodontics and Electronics.
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.