Ricardo Tapiador-Morales

16 papers receiving 345 citations

Peers

Ricardo Tapiador-Morales
Comparison fields: 5 of 64
  • Electrical and Electronic Engineering 198
  • Computer Vision and Pattern Recognition 140
  • Artificial Intelligence 82
  • Computer Networks and Communications 39
  • Biomedical Engineering 35
Replace Antonio Ríos-Navarro with:
Antonio Ríos-Navarro Spain
Taesik Na United States
Mayukh Nath United States
Daniel Bankman United States
Haruyoshi Yonekawa Japan
Daniel Gutiérrez-Galán Spain
F. Javier Toledo Spain
Huaxiang Lu China
Scott Koziol United States
Daniele Palossi Switzerland
Ricardo Tapiador-Morales relative to Antonio Ríos-Navarro Spain Antonio Ríos-Navarro's profile →
Citations per field
00.5×1.5×
Antonio Ríos-Navarro · 1×
Citations per year

Countries citing papers authored by Ricardo Tapiador-Morales

Since Specialization
Citations

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

Fields of papers citing papers by Ricardo Tapiador-Morales

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ricardo Tapiador-Morales. 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 Ricardo Tapiador-Morales. The network helps show where Ricardo Tapiador-Morales may publish in the future.

Co-authorship network of co-authors of Ricardo Tapiador-Morales

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

All Works

16 of 16 papers shown
#WorkIndexed citations
1 2
2 9
3 19
4 1
5 1
6 1
7 1
8 6
9 205
10 3
11 5
12 44
13 3
14 43
15 5
16 5

About Ricardo Tapiador-Morales

Ricardo Tapiador-Morales is a scholar working on Cellular and Molecular Neuroscience, Electrical and Electronic Engineering and Water Science and Technology, having authored 16 papers that have together received 353 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (11 papers), CCD and CMOS Imaging Sensors (8 papers) and Neuroscience and Neural Engineering (6 papers). The work is most often cited by research in Computational Mathematics (5 citations), Computer Vision and Pattern Recognition (140 citations) and Hardware and Architecture (24 citations). Ricardo Tapiador-Morales has collaborated with scholars based in Spain, Switzerland and Netherlands. Frequent co-authors include Alejandro Linares-Barranco, Antonio Ríos-Navarro, Tobi Delbrück, Hesham Mostafa, Federico Corradi, Moritz B. Milde, Shih‐Chii Liu, Ángel Jiménez-Fernández, Juan P. Dominguez‐Morales and Daniel Gutiérrez-Galán. Their work appears in journals such as Sensors, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.

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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