Jorge E. Camargo

673 total citations
35 papers, 358 citations indexed

About

Jorge E. Camargo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Sociology and Political Science. According to data from OpenAlex, Jorge E. Camargo has authored 35 papers receiving a total of 358 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 6 papers in Sociology and Political Science. Recurrent topics in Jorge E. Camargo's work include Image Retrieval and Classification Techniques (8 papers), Advanced Image and Video Retrieval Techniques (8 papers) and Video Analysis and Summarization (7 papers). Jorge E. Camargo is often cited by papers focused on Image Retrieval and Classification Techniques (8 papers), Advanced Image and Video Retrieval Techniques (8 papers) and Video Analysis and Summarization (7 papers). Jorge E. Camargo collaborates with scholars based in Colombia, United Kingdom and Switzerland. Jorge E. Camargo's co-authors include Fabio A. González, Juan C. Correa, Álvaro D. Orjuela-Cañón, Juan Carlos Caicedo, Luc Patiny, Jorge A. Vanegas, Carlos Arturo Torres Gastelú, Francisco Gómez, Pierre Esseiva and Julien Wist and has published in prestigious journals such as SHILAP Revista de lepidopterología, Information Sciences and Journal of the Operational Research Society.

In The Last Decade

Jorge E. Camargo

33 papers receiving 332 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jorge E. Camargo Colombia 9 92 86 70 50 38 35 358
Alexander A. Hernandez Philippines 13 73 0.8× 79 0.9× 118 1.7× 37 0.7× 9 0.2× 87 471
Ebin Deni Raj India 10 50 0.5× 133 1.5× 166 2.4× 44 0.9× 18 0.5× 46 520
Anwar Ur Rehman Italy 5 58 0.6× 70 0.8× 197 2.8× 31 0.6× 43 1.1× 13 388
Sameerchand Pudaruth Mauritius 9 56 0.6× 192 2.2× 51 0.7× 18 0.4× 36 0.9× 57 441
Al Amin Biswas Bangladesh 13 34 0.4× 108 1.3× 139 2.0× 33 0.7× 11 0.3× 27 459
Slamet Riyadi Indonesia 10 64 0.7× 97 1.1× 77 1.1× 18 0.4× 8 0.2× 152 436
Reza Rahutomo Indonesia 11 36 0.4× 63 0.7× 125 1.8× 14 0.3× 42 1.1× 40 380
Ernst Bekkering United States 8 37 0.4× 83 1.0× 30 0.4× 45 0.9× 11 0.3× 12 296
Dewa Made Sri Arsa Indonesia 9 63 0.7× 27 0.3× 112 1.6× 52 1.0× 7 0.2× 43 288
Kohei Arai Japan 12 47 0.5× 31 0.4× 80 1.1× 6 0.1× 20 0.5× 86 410

Countries citing papers authored by Jorge E. Camargo

Since Specialization
Citations

This map shows the geographic impact of Jorge E. Camargo'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 Jorge E. Camargo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jorge E. Camargo more than expected).

Fields of papers citing papers by Jorge E. Camargo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jorge E. Camargo. 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 Jorge E. Camargo. The network helps show where Jorge E. Camargo may publish in the future.

Co-authorship network of co-authors of Jorge E. Camargo

This figure shows the co-authorship network connecting the top 25 collaborators of Jorge E. Camargo. A scholar is included among the top collaborators of Jorge E. Camargo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jorge E. Camargo. Jorge E. Camargo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Camargo, Jorge E., et al.. (2025). Generative artificial intelligence (GenAI) use and dependence: an approach from behavioral economics. Frontiers in Public Health. 13. 1634121–1634121. 1 indexed citations
2.
Camargo, Jorge E., et al.. (2022). Social Engineering Detection Using Natural Language Processing and Machine Learning. 2067. 177–181. 1 indexed citations
3.
Camargo, Jorge E., et al.. (2021). Evaluating the impact of curriculum learning on the training process for an intelligent agent in a video game. SHILAP Revista de lepidopterología. 24(68). 1–20. 2 indexed citations
4.
Perdómo, Oscar, et al.. (2020). SOPHIA: System for Ophthalmic Image Acquisition, Transmission, and Intelligent Analysis. SHILAP Revista de lepidopterología. 29(54). e11769–e11769. 1 indexed citations
5.
Camargo, Jorge E., et al.. (2020). Modelo computacional para reconocimiento de lenguaje de señas en un contexto colombiano. SHILAP Revista de lepidopterología. 23(48). 197–232. 5 indexed citations
6.
Casarin, Roberto, Juan C. Correa, Jorge E. Camargo, et al.. (2019). What makes a tweet be retweeted? A Bayesian trigram analysis of tweet propagation during the 2015 Colombian political campaign. Journal of Information Science. 47(3). 297–305. 6 indexed citations
7.
Camargo, Jorge E., et al.. (2019). Characterization of citizens using word2vec and latent topic analysis in a large set of tweets. Cities. 92. 187–196. 41 indexed citations
8.
Camargo, Jorge E., et al.. (2019). A Content-Based Multi Label Classification Model to Suggest Tags for Posts in Stack Overflow. 176–187. 1 indexed citations
9.
10.
Orjuela-Cañón, Álvaro D., et al.. (2018). Tuberculosis diagnosis support analysis for precarious health information systems. Computer Methods and Programs in Biomedicine. 157. 11–17. 16 indexed citations
11.
Camargo, Jorge E., et al.. (2018). Sentiment polarity classification of tweets using a extended dictionary. INTELIGENCIA ARTIFICIAL. 21(62). 1–12. 3 indexed citations
12.
Correa, Juan C. & Jorge E. Camargo. (2017). Ideological Consumerism in Colombian Elections, 2015: Links Between Political Ideology, Twitter Activity, and Electoral Results. Cyberpsychology Behavior and Social Networking. 20(1). 37–43. 24 indexed citations
13.
Camargo, Jorge E., et al.. (2016). A big data analytics system to analyze citizens' perception of security. 1. 1–5. 7 indexed citations
14.
Camargo, Jorge E., et al.. (2015). Fine-tuning Deep Convolutional Networks for Plant Recognition.. CLEF (Working Notes). 135 indexed citations
15.
Camargo, Jorge E. & Fabio A. González. (2014). Multimodal visualization based on latent topic analysis. 1–6. 5 indexed citations
16.
Camargo, Jorge E. & Fabio A. González. (2013). MICS: Multimodal image collection summarization by optimal reconstruction subset selection. 13. 1–6. 1 indexed citations
17.
Vanegas, Jorge A., Juan Carlos Caicedo, Jorge E. Camargo, Raúl Ramos-Pollán, & Fabio A. González. (2012). Bioingenium at ImageCLEF 2012: Text and Visual Indexing for Medical Images.. 5 indexed citations
18.
Camargo, Jorge E., Pierre Esseiva, Fabio A. González, Julien Wist, & Luc Patiny. (2012). Monitoring of illicit pill distribution networks using an image collection exploration framework. Forensic Science International. 223(1-3). 298–305. 12 indexed citations
19.
Ramos-Pollán, Raúl, Fabio A. González, Juan Carlos Caicedo, et al.. (2012). BIGS: A framework for large-scale image processing and analysis over distributed and heterogeneous computing resources. 1–8. 8 indexed citations
20.
Camargo, Jorge E., et al.. (2010). A kernel-based strategy for exploratory image collection search. 1–6. 1 indexed citations

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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