David Meredith

1.2k citations
55 papers · 606 · h-index 14

Impact in

Papers in

David Meredith

52 papers receiving 534 citations

Peers

David Meredith
Comparison fields: 5 of 72
  • Signal Processing 397
  • Computer Vision and Pattern Recognition 379
  • Music 56
  • Cognitive Neuroscience 195
  • Artificial Intelligence 158
Replace Jean‐Claude Risset with:
Jean‐Claude Risset France
Samer Abdallah United Kingdom
Matija Marolt Slovenia
Barry Vercoe United States
Luís Gustavo Martins Portugal
F. Pachet France
Slim Essid France
Eric D. Scheirer United States
Ryuichi Oka Japan
Ju-Chiang Wang Taiwan
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Citations per field
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Citations per year

Countries citing papers authored by David Meredith

Since Specialization
Citations

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

Fields of papers citing papers by David Meredith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Meredith. 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 Meredith. The network helps show where David Meredith may publish in the future.

Co-authors

The 25 scholars most cited alongside David Meredith, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Meredith Line = papers co-authored together David Meredith links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002115
2 200254
3 202142
4 201535
5 200628
6
Pattern induction and matching in polyphonic music and other multidimensional datasets
200127
7 200221
8 199021
9 197220
10 200619
11 202017
12 200617
13 201616
14 201315
15 201513
16
A Three-Layer Approach for Music Retrieval in Large Databases
200112
17
COSIATEC and SIATECCompress: Pattern discovery by geometric compression
201312
18 197710
19 20148
20 19798

About David Meredith

David Meredith is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Cognitive Neuroscience and Computational Theory and Mathematics, having authored 55 papers that have together received 606 indexed citations. Recurring topics across this work include Music and Audio Processing (29 papers), Music Technology and Sound Studies (24 papers), Algorithms and Data Compression (14 papers), Neuroscience and Music Perception (8 papers), Advanced Algebra and Logic (3 papers), Video Analysis and Summarization (3 papers), Speech and Audio Processing (3 papers) and Image Processing and 3D Reconstruction (2 papers). The work is most often cited by research in Signal Processing (397 citations), Computer Vision and Pattern Recognition (379 citations), Music (56 citations), Cognitive Neuroscience (195 citations) and Artificial Intelligence (158 citations). David Meredith has collaborated with scholars based in Denmark, United Kingdom and United States. Frequent co-authors include Geraínt A. Wiggins, Kjell Lemström, Marcus T. Pearce, J. Roger Hindley, Tillman Weyde, E. A. Witmer, Anja Volk, Manolis Christodoulakis, Raphaël Clifford and Tim Crawford. Their work appears in journals such as Journal of New Music Research, Notre Dame Journal of Formal Logic, Nagoya Mathematical Journal, Computer Music Journal and Musicae Scientiae.

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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