Anne M. P. Canuto
- Artificial Intelligence top 2%
- Neural Networks and Applications 33
- Machine Learning and Data Classification 32
- Evolutionary Algorithms and Applications 27
- Metaheuristic Optimization Algorithms Research 26
- Fuzzy Logic and Control Systems 25
- Signal Processing top 5%
- Biometric Identification and Security 13
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- Face and Expression Recognition 25
- Information Systems top 5%
- Data Mining Algorithms and Applications 13
- Co-authors
- Marcílio C. P. de SoutoAndré L. V. CoelhoRegivan SantiagoMárjory Da Costa‐AbreuRodrigo G. F. SoaresMichael FairhurstBenjamín BedregalGareth Howells
- Journals
- Expert Systems with Applications (4 papers)IEEE Access (2 papers)Information Sciences (1 paper)
- Partner nations
- BrazilUnited KingdomUnited States
In The Last Decade
Anne M. P. Canuto
125 papers receiving 906 citations
Peers
Comparison fields: 5 of 111
- Artificial Intelligence 619
- Signal Processing 141
- Computer Vision and Pattern Recognition 254
- Information Systems 192
- Computational Theory and Mathematics 88
Countries citing papers authored by Anne M. P. Canuto
This map shows the geographic impact of Anne M. P. Canuto'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 Anne M. P. Canuto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anne M. P. Canuto more than expected).
Fields of papers citing papers by Anne M. P. Canuto
This network shows the impact of papers produced by Anne M. P. Canuto. 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 Anne M. P. Canuto. The network helps show where Anne M. P. Canuto may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Anne M. P. Canuto, 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 | 2022 | 0 | |
| 2 | 2022 | 0 | |
| 3 | 2020 | 2 | |
| 4 | 2020 | 3 | |
| 5 | 2019 | 2 | |
| 6 | 2019 | 0 | |
| 7 | 2018 | 3 | |
| 8 | 2017 | 1 | |
| 9 | 2015 | 1 | |
| 10 | 2011 | 1 | |
| 11 | 2011 | 7 | |
| 12 | 2008 | 16 | |
| 13 | 2008 | 2 | |
| 14 | 2008 | 1 | |
| 15 | 2006 | 3 | |
| 16 | 2006 | 11 | |
| 17 | 2006 | 10 | |
| 18 | 2004 | 4 | |
| 19 | Network Combination Strategies for a Hybrid Neuro-Fuzzy Multi-Expert System | 2000 | 1 |
| 20 | A Comparative Performance Evaluation of the RePart Neuro-Fuzzy Network | 1999 | 1 |
About Anne M. P. Canuto
Anne M. P. Canuto is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 135 papers that have together received 935 indexed citations. Recurring topics across this work include Neural Networks and Applications (33 papers), Machine Learning and Data Classification (32 papers), Evolutionary Algorithms and Applications (27 papers), Metaheuristic Optimization Algorithms Research (26 papers), Face and Expression Recognition (25 papers), Fuzzy Logic and Control Systems (25 papers), Data Mining Algorithms and Applications (13 papers) and Biometric Identification and Security (13 papers). The work is most often cited by research in Artificial Intelligence (619 citations), Signal Processing (141 citations) and Computer Vision and Pattern Recognition (254 citations). Anne M. P. Canuto has collaborated with scholars based in Brazil, United Kingdom and United States. Frequent co-authors include Marcílio C. P. de Souto, André L. V. Coelho, Regivan Santiago, Márjory Da Costa‐Abreu, Rodrigo G. F. Soares, Michael Fairhurst, Benjamín Bedregal, Gareth Howells, Marco C. Goldbarg and Elizabeth Ferreira Gouvêa Goldbarg. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Information Sciences.
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.