Marco Flores-Calero

96 total papers · 1.1k total citations
50 papers, 599 citations indexed

About

Marco Flores-Calero is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Marco Flores-Calero has authored 50 papers receiving a total of 599 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 9 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Marco Flores-Calero's work include ECG Monitoring and Analysis (8 papers), Video Surveillance and Tracking Methods (7 papers) and Machine Learning and ELM (5 papers). Marco Flores-Calero is often cited by papers focused on ECG Monitoring and Analysis (8 papers), Video Surveillance and Tracking Methods (7 papers) and Machine Learning and ELM (5 papers). Marco Flores-Calero collaborates with scholars based in Ecuador, Spain and Chile. Marco Flores-Calero's co-authors include José María Armingol, Arturo de la Escalera, Brajesh Kumar, Karla Vizuete, Alexis Debut, Fernanda Pilaquinga, Éric Yiou, S. Bouisset, David Zabala‐Blanco and Jens Maiero and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.

In The Last Decade

Marco Flores-Calero

45 papers receiving 560 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Marco Flores-Calero	143	118	92	88	73	50	599
Shichao Wu	183 1.3×	70 0.6×	87 0.9×	18 0.2×	23 0.3×	28	505
Baoxin Li	19 0.1×	191 1.6×	48 0.5×	37 0.4×	39 0.5×	37	687
Zilu Liang	223 1.6×	74 0.6×	78 0.8×	19 0.2×	9 0.1×	81	651
Cong Wang	78 0.5×	52 0.4×	88 1.0×	76 0.9×	247 3.4×	31	675
Hazry Desa	57 0.4×	163 1.4×	95 1.0×	17 0.2×	33 0.5×	109	634
Ling Huang	29 0.2×	35 0.3×	121 1.3×	23 0.3×	119 1.6×	49	614
Zuojin Li	242 1.7×	47 0.4×	67 0.7×	99 1.1×	90 1.2×	39	593
Chongyang Wang	194 1.4×	283 2.4×	78 0.8×	26 0.3×	6 0.1×	48	653
Jaeyeon Lee	28 0.2×	204 1.7×	169 1.8×	56 0.6×	26 0.4×	72	655
Yong-Guk Kim	93 0.7×	207 1.8×	63 0.7×	60 0.7×	43 0.6×	59	591

Countries citing papers authored by Marco Flores-Calero

Since Specialization

Citations

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

Fields of papers citing papers by Marco Flores-Calero

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco Flores-Calero. 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 Marco Flores-Calero. The network helps show where Marco Flores-Calero may publish in the future.

Co-authorship network of co-authors of Marco Flores-Calero

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Flores-Calero. A scholar is included among the top collaborators of Marco Flores-Calero 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 Marco Flores-Calero. Marco Flores-Calero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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