Alberto Cano
- Computer Science Applications top 0.5%
- Artificial Intelligence top 0.5%
- Machine Learning and Data Classification 27
- Data Stream Mining Techniques 25
- Text and Document Classification Technologies 15
- Evolutionary Algorithms and Applications 14
- Metaheuristic Optimization Algorithms Research 13
- Imbalanced Data Classification Techniques 10
- Anomaly Detection Techniques and Applications 10
- Signal Processing top 2%
- Information Systems top 2%
- Data Mining Algorithms and Applications 10
- Co-authors
- Sebastián VenturaBartosz KrawczykYoucef DjenouriAsma BelhadiJerry Chun‐Wei LinAmelia ZafraCristóbal RomeroJoaquín Bautista Valhondo
- Partner nations
- United StatesSpainNorway
In The Last Decade
Alberto Cano
85 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 134
- Computer Science Applications 362
- Artificial Intelligence 1.7k
- Signal Processing 277
- Health Information Management 102
- Information Systems 448
Countries citing papers authored by Alberto Cano
This map shows the geographic impact of Alberto Cano'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 Alberto Cano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alberto Cano more than expected).
Fields of papers citing papers by Alberto Cano
This network shows the impact of papers produced by Alberto Cano. 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 Alberto Cano. The network helps show where Alberto Cano may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Alberto Cano, 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 | 2026 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 4 | |
| 5 | 2021 | 9 | |
| 6 | 2021 | 21 | |
| 7 | 2021 | 34 | |
| 8 | 2020 | 46 | |
| 9 | 2020 | 0 | |
| 10 | 2020 | 25 | |
| 11 | 2019 | 85 | |
| 12 | 2019 | 58 | |
| 13 | 2019 | 14 | |
| 14 | 2019 | 31 | |
| 15 | 2019 | 50 | |
| 16 | 2019 | 97 | |
| 17 | 2018 | 41 | |
| 18 | 2018 | 13 | |
| 19 | 2015 | 34 | |
| 20 | 2015 | 200 |
About Alberto Cano
Alberto Cano is a scholar working on Artificial Intelligence, Signal Processing, Industrial and Manufacturing Engineering, Information Systems and Computer Vision and Pattern Recognition, having authored 93 papers that have together received 2.6k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (27 papers), Data Stream Mining Techniques (25 papers), Text and Document Classification Technologies (15 papers), Evolutionary Algorithms and Applications (14 papers), Metaheuristic Optimization Algorithms Research (13 papers), Data Mining Algorithms and Applications (10 papers), Imbalanced Data Classification Techniques (10 papers) and Anomaly Detection Techniques and Applications (10 papers). The work is most often cited by research in Computer Science Applications (362 citations), Artificial Intelligence (1.7k citations), Signal Processing (277 citations), Health Information Management (102 citations) and Information Systems (448 citations). Alberto Cano has collaborated with scholars based in United States, Spain and Norway. Frequent co-authors include Sebastián Ventura, Bartosz Krawczyk, Youcef Djenouri, Asma Belhadi, Jerry Chun‐Wei Lin, Amelia Zafra, Cristóbal Romero, Joaquín Bautista Valhondo, Djamel Djenouri and José María Luna. Their work appears in journals such as Information Sciences, IEEE Access, Knowledge-Based Systems, Machine Learning and Neurocomputing.
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.