Edgar Acuña
Impact in
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- Insect and Pesticide Research
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- Anomaly Detection Techniques and Applications
Papers in
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- Imbalanced Data Classification Techniques 2
- Anomaly Detection Techniques and Applications 2
- Machine Learning and Data Classification 2
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- Plant and animal studies 2
- Co-authors
- Rémi Mégret (2 shared papers)Tuğrul Giray (2 shared papers)José L. Agosto‐Rivera (2 shared papers)Jorge G. Arroyo (1 shared paper)Rubén A. Quintero (1 shared paper)Kristin Branson (1 shared paper)Mary Allen (1 shared paper)Héctor René Vega-Carrillo (1 shared paper)
- Journals
- Big Data and Cognitive Computing (1 paper)Lasers in Surgery and Medicine (1 paper)Revista Mexicana de Física (1 paper)
- Partner nations
- Puerto RicoUnited StatesMexico
In The Last Decade
Edgar Acuña
9 papers receiving 105 citations
Peers
Comparison fields: 5 of 50
- Insect Science 27
- Artificial Intelligence 48
- Genetics 29
- Ecology, Evolution, Behavior and Systematics 20
- Health Information Management 4
Countries citing papers authored by Edgar Acuña
This map shows the geographic impact of Edgar Acuña'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 Edgar Acuña with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edgar Acuña more than expected).
Fields of papers citing papers by Edgar Acuña
This network shows the impact of papers produced by Edgar Acuña. 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 Edgar Acuña. The network helps show where Edgar Acuña may publish in the future.
Co-authors
The 12 scholars most cited alongside Edgar Acuña, 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 | 2006 | 40 | |
| 2 | 2018 | 31 | |
| 3 | 2023 | 11 | |
| 4 | Honeybee Detection and Pose Estimation using Convolutional Neural Networks | 2018 | 10 |
| 5 | 1999 | 9 | |
| 6 | Características dosimétricas de fuentes isotópicas de neutrones | 2005 | 5 |
| 7 | Parallel computation of kernel density estimates classifiers and their ensembles | 2003 | 3 |
| 8 | An Algorithm for Detecting Noise on Supervised | 2007 | 2 |
| 9 | 2013 | 1 | |
| 10 | 2023 | 0 | |
| 11 | 2024 | 0 |
About Edgar Acuña
Edgar Acuña is a scholar working on Artificial Intelligence, Ecology, Evolution, Behavior and Systematics, Insect Science, Computer Networks and Communications and Pediatrics, Perinatology and Child Health, having authored 11 papers that have together received 112 indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (2 papers), Plant and animal studies (2 papers), Anomaly Detection Techniques and Applications (2 papers), Machine Learning and Data Classification (2 papers), Insect and Pesticide Research (2 papers), Diabetes Management and Research (1 paper), Artificial Intelligence in Healthcare (1 paper) and Spam and Phishing Detection (1 paper). The work is most often cited by research in Insect Science (27 citations), Artificial Intelligence (48 citations), Genetics (29 citations), Ecology, Evolution, Behavior and Systematics (20 citations) and Health Information Management (4 citations). Edgar Acuña has collaborated with scholars based in Puerto Rico, United States and Mexico. Frequent co-authors include Rémi Mégret, Tuğrul Giray, José L. Agosto‐Rivera, Jorge G. Arroyo, Rubén A. Quintero, Kristin Branson, Mary Allen, Héctor René Vega-Carrillo, Eduardo Gallego and Robert Furstenberg. Their work appears in journals such as Big Data and Cognitive Computing, Lasers in Surgery and Medicine and Revista Mexicana de Física.
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.