Edgar Acuña

729 citations
15 papers · 555 · h-index 6

Impact in

Papers in

    • Machine Learning and Data Classification 4
    • Neural Networks and Applications 3
    • Imbalanced Data Classification Techniques 2
    • Anomaly Detection Techniques and Applications 2
    • Evolutionary Algorithms and Applications 2

Edgar Acuña

13 papers receiving 514 citations

Peers

Edgar Acuña
Comparison fields: 5 of 128
  • Health Information Management 40
  • Artificial Intelligence 232
  • Statistics and Probability 46
  • Signal Processing 56
  • Information Systems 93
Replace Janusz Wojtusiak with:
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Citations per field
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Citations per year

Countries citing papers authored by Edgar Acuña

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 13 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.

Border = papers with Edgar Acuña Line = papers co-authored together Edgar Acuña links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2004423
2 200646
3 201835
4 202311
5
Honeybee Detection and Pose Estimation using Convolutional Neural Networks
201811
6 199910
7
Características dosimétricas de fuentes isotópicas de neutrones
20055
8
Parallel computation of kernel density estimates classifiers and their ensembles
20034
9 20114
10 20112
11
An Algorithm for Detecting Noise on Supervised
20072
12 20131
13 20021
14 20230
15 20240

About Edgar Acuña

Edgar Acuña is a scholar working on Artificial Intelligence, Information Systems, Ecology, Evolution, Behavior and Systematics, Insect Science and Computer Networks and Communications, having authored 15 papers that have together received 555 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (4 papers), Neural Networks and Applications (3 papers), Imbalanced Data Classification Techniques (2 papers), Plant and animal studies (2 papers), Anomaly Detection Techniques and Applications (2 papers), Evolutionary Algorithms and Applications (2 papers), Insect and Pesticide Research (2 papers) and Diabetes Management and Research (1 paper). The work is most often cited by research in Health Information Management (40 citations), Artificial Intelligence (232 citations), Statistics and Probability (46 citations), Signal Processing (56 citations) and Information Systems (93 citations). Edgar Acuña has collaborated with scholars based in Puerto Rico, United States and Mexico. Frequent co-authors include Tuğrul Giray, José L. Agosto‐Rivera, Rémi Mégret, Kristin Branson, Rubén A. Quintero, Mary Allen, Jorge G. Arroyo, Eduardo Gallego, Héctor René Vega-Carrillo and A. Rojas. Their work appears in journals such as Big Data and Cognitive Computing, Lasers in Surgery and Medicine, Lecture notes in computer science, Revista Mexicana de Física and International Encyclopedia of Statistical 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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