David Rizo
Impact in
- Signal Processing top 2%
- Music and Audio Processing
- Speech and Audio Processing
- Music top 5%
- Diverse Musicological Studies
Papers in
-
- Music and Audio Processing 42
- Speech and Audio Processing 6
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- Music Technology and Sound Studies 31
- Handwritten Text Recognition Techniques 9
- Video Analysis and Summarization 3
- Co-authors
- Jorge Calvo-Zaragoza (13 shared papers)Jose Manuel Iñesta (27 shared papers)Antonio Pertusa (2 shared papers)Kjell Lemström (3 shared papers)Amaury Habrard (1 shared paper)Marc Sebban (1 shared paper)Nicola Orio (3 shared papers)Markus Schedl (1 shared paper)
In The Last Decade
David Rizo
44 papers receiving 337 citations
Peers
Comparison fields: 5 of 31
- Signal Processing 333
- Music 49
- Computer Vision and Pattern Recognition 301
- Cognitive Neuroscience 64
- Developmental Biology 5
Countries citing papers authored by David Rizo
This map shows the geographic impact of David Rizo'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 David Rizo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Rizo more than expected).
Fields of papers citing papers by David Rizo
This network shows the impact of papers produced by David Rizo. 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 David Rizo. The network helps show where David Rizo may publish in the future.
Co-authors
The 19 scholars most cited alongside David Rizo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 67 | |
| 2 | 2009 | 36 | |
| 3 | 2006 | 27 | |
| 4 | 2016 | 17 | |
| 5 | HARMONIC, MELODIC, AND FUNCTIONAL AUTOMATIC ANALYSIS | 2007 | 17 |
| 6 | 2023 | 16 | |
| 7 | 2008 | 16 | |
| 8 | 2011 | 15 | |
| 9 | 2018 | 13 | |
| 10 | 2016 | 11 | |
| 11 | Tree model of symbolic music for tonality guessing | 2006 | 10 |
| 12 | 2003 | 9 | |
| 13 | Tree-structured Representation of Melodies for Comparison and Retrieval | 2002 | 8 |
| 14 | 2018 | 8 | |
| 15 | 2021 | 7 | |
| 16 | 2008 | 6 | |
| 17 | 2009 | 6 | |
| 18 | 2011 | 6 | |
| 19 | 2007 | 6 | |
| 20 | 2021 | 5 |
About David Rizo
David Rizo is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Music, Artificial Intelligence and Cognitive Neuroscience, having authored 46 papers that have together received 362 indexed citations. Recurring topics across this work include Music and Audio Processing (42 papers), Music Technology and Sound Studies (31 papers), Handwritten Text Recognition Techniques (9 papers), Diverse Musicological Studies (7 papers), Speech and Audio Processing (6 papers), Algorithms and Data Compression (5 papers), Neuroscience and Music Perception (5 papers) and Video Analysis and Summarization (3 papers). The work is most often cited by research in Signal Processing (333 citations), Music (49 citations), Computer Vision and Pattern Recognition (301 citations), Cognitive Neuroscience (64 citations) and Developmental Biology (5 citations). David Rizo has collaborated with scholars based in Spain, Finland and Canada. Frequent co-authors include Jorge Calvo-Zaragoza, Jose Manuel Iñesta, Antonio Pertusa, Kjell Lemström, Amaury Habrard, Marc Sebban, Nicola Orio, Markus Schedl, Riccardo Miotto and Alan A. Marsden. Their work appears in journals such as Applied Sciences, Journal of New Music Research, International Journal on Document Analysis and Recognition (IJDAR), International Journal on Digital Libraries and Journal of Mathematics and Music.
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.