MCYT baseline corpus: a bimodal biometric database

Abstract

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About

This paper, published in 1950, received 481 indexed citations. Written by Javier Ortega-García, Julián Fiérrez, J. M. Gonzalez, Marcos Faúndez-Zanuy, Inma Hernáez, Juan J. Igarza, Carlos Vivaracho‐Pascual and David Escudero-Mancebo covering the research area of Information Systems, Computer Vision and Pattern Recognition and Signal Processing. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (405 citations), Signal Processing (201 citations) and Artificial Intelligence (173 citations). Published in IEE Proceedings - Vision Image and Signal Processing.

Countries where authors are citing MCYT baseline corpus: a bimodal biometric database

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Citations

This map shows the geographic impact of MCYT baseline corpus: a bimodal biometric database. 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 MCYT baseline corpus: a bimodal biometric database with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites MCYT baseline corpus: a bimodal biometric database more than expected).

Fields of papers citing MCYT baseline corpus: a bimodal biometric database

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of MCYT baseline corpus: a bimodal biometric database. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the MCYT baseline corpus: a bimodal biometric database.

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.

This paper is also available at doi.org/10.1049/ip-vis:20031078.

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