David Cope

50 papers receiving 631 citations

Peers

David Cope
Comparison fields: 5 of 105
  • Signal Processing 405
  • Computer Vision and Pattern Recognition 460
  • Cognitive Neuroscience 297
  • Music 41
  • Architecture 8
Replace Mathieu Barthet with:
Mathieu Barthet United Kingdom
Amílcar Cardoso Portugal
Dan Trueman United States
Nicola Orio Italy
Matthew Yee-King United Kingdom
Goffredo Haus Italy
David Ackermann Germany
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Ichiro Fujinaga Canada
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Citations per field
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Citations per year

Countries citing papers authored by David Cope

Since Specialization
Citations

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

Fields of papers citing papers by David Cope

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside David Cope, 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 Cope Line = papers co-authored together David Cope links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997172
2
Virtual Music: Computer Synthesis of Musical Style
200177
3 199267
4 200159
5 198750
6
The Algorithmic Composer
200041
7 198937
8 200821
9 200620
10 200420
11 199819
12 200819
13 199117
14 200315
15
Pattern Matching as an Engine for the Computer Simulation of Musical Style
199011
16 19979
17 19867
18 20077
19
Signatures and earmarks: computer recognition of patterns in music
19986
20 20146

About David Cope

David Cope is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Cognitive Neuroscience, Music and Control and Systems Engineering, having authored 63 papers that have together received 763 indexed citations. Recurring topics across this work include Music Technology and Sound Studies (22 papers), Music and Audio Processing (19 papers), Neuroscience and Music Perception (11 papers), Musicology and Musical Analysis (4 papers), Diverse Musicological Studies (3 papers), Industrial Technology and Control Systems (2 papers), Electrical Contact Performance and Analysis (2 papers) and Species Distribution and Climate Change (2 papers). The work is most often cited by research in Signal Processing (405 citations), Computer Vision and Pattern Recognition (460 citations), Cognitive Neuroscience (297 citations), Music (41 citations) and Architecture (8 citations). David Cope has collaborated with scholars based in United States, United Kingdom and Norway. Frequent co-authors include Andrew D. Wright, Mansooreh Mollaghasemi, Christopher J. Corcoran, Kenneth A. Pasch, David S. Fischer, Stefan Kostka, Louis Kaplow, Ghaith Rabadi, Probjot Singh and William H. Thomason. Their work appears in journals such as Computer Music Journal, Notes, SAE technical papers on CD-ROM/SAE technical paper series, Minerva and Journal of Simulation.

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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