David Rizo

513 total citations
33 papers, 212 citations indexed

About

David Rizo is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, David Rizo has authored 33 papers receiving a total of 212 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computer Vision and Pattern Recognition, 30 papers in Signal Processing and 8 papers in Artificial Intelligence. Recurrent topics in David Rizo's work include Music and Audio Processing (30 papers), Music Technology and Sound Studies (23 papers) and Handwritten Text Recognition Techniques (7 papers). David Rizo is often cited by papers focused on Music and Audio Processing (30 papers), Music Technology and Sound Studies (23 papers) and Handwritten Text Recognition Techniques (7 papers). David Rizo collaborates with scholars based in Spain, Italy and Canada. David Rizo's co-authors include José M. Iñesta, Jorge Calvo-Zaragoza, Antonio Pertusa, Alan Marsden, Nicola Orio, Kjell Lemström, Riccardo Miotto, Markus Schedl, Olivier Lartillot and Nicola Montecchio and has published in prestigious journals such as SHILAP Revista de lepidopterología, Pattern Recognition and Applied Sciences.

In The Last Decade

David Rizo

30 papers receiving 194 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Rizo Spain	8	198	176	38	37	35	33	212
Sebastian Streich Spain	7	235 1.2×	190 1.1×	19 0.5×	33 0.9×	13 0.4×	12	242
Alastair Porter Spain	9	253 1.3×	160 0.9×	59 1.6×	52 1.4×	55 1.6×	20	280
Eric Allamanche Germany	8	296 1.5×	246 1.4×	45 1.2×	22 0.6×	10 0.3×	12	325
Deshun Yang China	9	196 1.0×	130 0.7×	60 1.6×	54 1.5×	33 0.9×	29	231
Andreas Arzt Austria	10	190 1.0×	173 1.0×	15 0.4×	49 1.3×	23 0.7×	19	207
Giorgio Zoia Switzerland	5	261 1.3×	209 1.2×	37 1.0×	51 1.4×	25 0.7×	22	290
Oliver Hellmuth Germany	9	259 1.3×	158 0.9×	27 0.7×	60 1.6×	8 0.2×	18	276
Curtis Hawthorne United States	7	185 0.9×	183 1.0×	55 1.4×	81 2.2×	15 0.4×	9	239
Tetsuro Kitahara Japan	10	290 1.5×	200 1.1×	62 1.6×	40 1.1×	21 0.6×	34	304
Filip Korzeniowski Austria	6	163 0.8×	157 0.9×	19 0.5×	51 1.4×	18 0.5×	12	192

Countries citing papers authored by David Rizo

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of David Rizo

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Rizo, David, et al.. (2025). Aligned music notation and lyrics transcription. Pattern Recognition. 170. 112094–112094.

2.

Rizo, David, et al.. (2023). End-to-end optical music recognition for pianoform sheet music. International Journal on Document Analysis and Recognition (IJDAR). 26(3). 347–362. 6 indexed citations

3.

Esplà-Gomis, Miquel, et al.. (2021). Applying Automatic Translation for Optical Music Recognition’s Encoding Step. Applied Sciences. 11(9). 3890–3890. 2 indexed citations

4.

Rizo, David & Alan Marsden. (2018). An MEI-based standard encoding for hierarchical music analyses. International Journal on Digital Libraries. 20(1). 93–105. 3 indexed citations

5.

Rizo, David, Jorge Calvo-Zaragoza, & José M. Iñesta. (2018). MuRET. 52–56. 6 indexed citations

6.

Calvo-Zaragoza, Jorge & David Rizo. (2018). Camera-PrIMuS: Neural End-to-End Optical Music Recognition on Realistic Monophonic Scores. Zenodo (CERN European Organization for Nuclear Research). 248–255. 10 indexed citations

7.

Rizo, David, et al.. (2017). Hacia la codificación digital de la notación mensural blanca hispánica. SHILAP Revista de lepidopterología. 293–304. 1 indexed citations

8.

Calvo-Zaragoza, Jorge, et al.. (2017). Pen-Based Music Document Transcription. 21–22. 1 indexed citations

9.

Calvo-Zaragoza, Jorge, David Rizo, & José M. Iñesta. (2016). Two (Note) Heads Are Better Than One: Pen-Based Multimodal Interaction With Music Scores.. International Symposium/Conference on Music Information Retrieval. 509–514. 14 indexed citations

10.

Rizo, David & Alan Marsden. (2016). A standard format proposal for hierarchical analyses and representations. 25–32. 4 indexed citations

11.

Orio, Nicola & David Rizo. (2011). Overview of MusiCLEF 2011. Research Padua Archive (University of Padua). 1 indexed citations

12.

Iñesta, José M., et al.. (2011). Melodic Identification Using Probabilistic Tree Automata. Journal of New Music Research. 40(2). 93–103. 3 indexed citations

13.

Rizo, David, et al.. (2010). Genre classification of music by tonal harmony. Intelligent Data Analysis. 14(5). 533–545. 1 indexed citations

14.

Ramírez, Rafael, Alfonso Pérez, Esteban Maestre, et al.. (2008). Modeling Celtic Violin Expressive Performance. International Conference on Machine Learning. 1 indexed citations

15.

Rizo, David, et al.. (2008). Learning to analyse tonal music. RUA, Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante).

16.

Rizo, David, et al.. (2007). HARMONIC, MELODIC, AND FUNCTIONAL AUTOMATIC ANALYSIS. The Journal of the Abraham Lincoln Association. 2007. 11 indexed citations

17.

Rizo, David, et al.. (2006). Melody Track Identification in Music Symbolic Files.. The Florida AI Research Society. 254–259. 1 indexed citations

18.

Rizo, David, et al.. (2006). Tree model of symbolic music for tonality guessing. 299–304. 4 indexed citations

19.

Rizo, David, et al.. (2006). A Pattern Recognition Approach For Melody Track Selection In Midi Files.. Zenodo (CERN European Organization for Nuclear Research). 61–66. 22 indexed citations

20.

Rizo, David & José M. Iñesta. (2002). Tree-structured Representation of Melodies for Comparison and Retrieval. 140–155. 5 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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