Fábio M. Bayer

95 papers and 1.2k indexed citations i.

About

Fábio M. Bayer is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Statistics and Probability. According to data from OpenAlex, Fábio M. Bayer has authored 95 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Computer Vision and Pattern Recognition, 33 papers in Signal Processing and 25 papers in Statistics and Probability. Recurrent topics in Fábio M. Bayer’s work include Digital Filter Design and Implementation (32 papers), Advanced Data Compression Techniques (29 papers) and Image and Signal Denoising Methods (22 papers). Fábio M. Bayer is often cited by papers focused on Digital Filter Design and Implementation (32 papers), Advanced Data Compression Techniques (29 papers) and Image and Signal Denoising Methods (22 papers). Fábio M. Bayer collaborates with scholars based in Brazil, United States and Canada. Fábio M. Bayer's co-authors include Renato J. Cintra, Arjuna Madanayake, Francisco Cribari‐Neto, Alice Kozakevicius, Thiago L. T. da Silveira, Paolo Gamba, Renato Machado, Vassil S. Dimitrov, Mats I. Pettersson and André Ferreira Leite and has published in prestigious journals such as PLoS ONE, Journal of Hydrology and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Co-authorship network of co-authors of Fábio M. Bayer i

Fields of papers citing papers by Fábio M. Bayer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fábio M. Bayer. 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 Fábio M. Bayer. The network helps show where Fábio M. Bayer may publish in the future.

Countries citing papers authored by Fábio M. Bayer

Since Specialization
Citations

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

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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2025