Marco Mora

1.3k total citations · 1 hit paper
64 papers, 810 citations indexed

About

Marco Mora is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Plant Science. According to data from OpenAlex, Marco Mora has authored 64 papers receiving a total of 810 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 13 papers in Plant Science. Recurrent topics in Marco Mora's work include Machine Learning and ELM (18 papers), Spectroscopy and Chemometric Analyses (9 papers) and Horticultural and Viticultural Research (8 papers). Marco Mora is often cited by papers focused on Machine Learning and ELM (18 papers), Spectroscopy and Chemometric Analyses (9 papers) and Horticultural and Viticultural Research (8 papers). Marco Mora collaborates with scholars based in Chile, Argentina and Spain. Marco Mora's co-authors include Claudio Fredes, Ricardo J. Barrientos, Ruber Hernández-García, José Naranjo-Torres, Matilde Santos, Marcos Carrasco-Benavides, Sigfredo Fuentes, David Zabala‐Blanco, Boris Lucero and Fernando Córdova‐Lepe and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Marco Mora

61 papers receiving 763 citations

Hit Papers

A Review of Convolutional Neural Network Applied to Fruit... 2020 2026 2022 2024 2020 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Review of Convolutional Neural Network Applied to Fruit Image Processing
    2020 260 citations José Naranjo-Torres, Marco Mora et al. Applied Sciences profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco Mora Chile 15 274 192 172 134 83 64 810
Ashish Kumar Tripathi India 17 305 1.1× 283 1.5× 170 1.0× 94 0.7× 45 0.5× 44 1000
Jinrong He China 14 525 1.9× 135 0.7× 146 0.8× 237 1.8× 92 1.1× 71 1.0k
Guan Wang China 12 574 2.1× 228 1.2× 326 1.9× 217 1.6× 123 1.5× 42 1.4k
Kemal Adem Türkiye 13 301 1.1× 250 1.3× 159 0.9× 135 1.0× 51 0.6× 47 877
Arnab Kumar Maji India 17 522 1.9× 250 1.3× 129 0.8× 183 1.4× 77 0.9× 70 1.3k
Mohit Agarwal India 16 722 2.6× 159 0.8× 163 0.9× 280 2.1× 90 1.1× 55 1.4k
Udo Seiffert Germany 20 518 1.9× 229 1.2× 101 0.6× 224 1.7× 214 2.6× 88 1.1k
Zhaohui Jiang China 14 382 1.4× 93 0.5× 99 0.6× 133 1.0× 75 0.9× 49 816
Yan Zhou China 16 119 0.4× 147 0.8× 284 1.7× 56 0.4× 32 0.4× 121 955
Kemal Akyol Türkiye 9 494 1.8× 151 0.8× 130 0.8× 198 1.5× 76 0.9× 47 1.0k

Countries citing papers authored by Marco Mora

Since Specialization
Citations

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

Fields of papers citing papers by Marco Mora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Mora

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Mora. A scholar is included among the top collaborators of Marco Mora 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 Mora. Marco Mora 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.
Mora, Marco, et al.. (2025). A review of neural networks for metagenomic binning. Briefings in Bioinformatics. 26(2). 2 indexed citations
2.
Mora, Marco, et al.. (2024). A Review on Large-Scale Data Processing with Parallel and Distributed Randomized Extreme Learning Machine Neural Networks. Mathematical and Computational Applications. 29(3). 40–40. 2 indexed citations
3.
Barrientos, Ricardo J., et al.. (2024). Parallel ensemble of a randomization-based online sequential neural network for classification problems using a frequency criterion. Scientific Reports. 14(1). 16104–16104. 1 indexed citations
4.
Mora, Marco, et al.. (2023). Detection of Parkinson’s disease based on spectrograms of voice recordings and Extreme Learning Machine random weight neural networks. Engineering Applications of Artificial Intelligence. 125. 106700–106700. 14 indexed citations
5.
Mora, Marco, et al.. (2023). A comprehensive review of extreme learning machine on medical imaging. Neurocomputing. 556. 126618–126618. 12 indexed citations
6.
Mora, Marco, et al.. (2023). Estimation of the optimal number of neurons in extreme learning machine using simulated annealing and the golden section. Journal of Physics Conference Series. 2515(1). 12003–12003. 1 indexed citations
7.
Mora, Marco, et al.. (2023). A Review of multilayer extreme learning machine neural networks. Artificial Intelligence Review. 56(11). 13691–13742. 14 indexed citations
8.
Mora, Marco, et al.. (2023). Metagenomic Binning based on Unsupervised Extreme Learning Machine. 1–6. 1 indexed citations
9.
Mora, Marco, et al.. (2022). Automated diagnosis of schizophrenia using EEG microstates and Deep Convolutional Neural Network. Expert Systems with Applications. 209. 118236–118236. 25 indexed citations
10.
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12.
Mora, Marco, et al.. (2022). Training of an Extreme Learning Machine Autoencoder Based on an Iterative Shrinkage-Thresholding Optimization Algorithm. Applied Sciences. 12(18). 9021–9021. 2 indexed citations
13.
Zabala‐Blanco, David, Marco Mora, César A. Azurdia-Meza, et al.. (2021). Multilayer Extreme Learning Machine as Equalizer in OFDM-based Radio-over-fiber Systems. IEEE Latin America Transactions. 19(10). 1790–1797. 4 indexed citations
14.
Zabala‐Blanco, David, Marco Mora, César A. Azurdia-Meza, et al.. (2020). Relaxation of the Radio-Frequency Linewidth for Coherent-Optical Orthogonal Frequency-Division Multiplexing Schemes by Employing the Improved Extreme Learning Machine. Symmetry. 12(4). 632–632. 12 indexed citations
15.
Zabala‐Blanco, David, Marco Mora, Ricardo J. Barrientos, Ruber Hernández-García, & José Naranjo-Torres. (2020). Fingerprint Classification through Standard and Weighted Extreme Learning Machines. Applied Sciences. 10(12). 4125–4125. 18 indexed citations
16.
Mora, Marco, et al.. (2018). Off-line writer verification based on simple graphemes. Pattern Recognition. 79. 414–426. 21 indexed citations
17.
Carrasco-Benavides, Marcos, et al.. (2016). Assessment of an automated digital method to estimate leaf area index ( LAI ) in cherry trees. New Zealand Journal of Crop and Horticultural Science. 44(4). 247–261. 14 indexed citations
18.
Mora, Marco, et al.. (2014). Fruit Maturity Estimation based on Color Scales. El Servicio de Difusión de la Creación Intelectual (National University of La Plata). 2 indexed citations
19.
Mora, Marco, et al.. (2014). A method to estimate Grape Phenolic Maturity based on seed images. Computers and Electronics in Agriculture. 101. 76–83. 15 indexed citations
20.
Mora, Marco, et al.. (2010). Morphological Color Images Processing Using Distance-Based and Lexicographic Order Operators. 8. 258–264. 7 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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