Jeffrey J. Scott
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 5%
- Cognitive Neuroscience top 10%
- Artificial Intelligence
- Experimental and Cognitive Psychology
- Co-authors
- Youngmoo E. KimErik M. SchmidtRaymond MignecoBrandon G. MortonPatrick RichardsonDouglas TurnbullSang Won LeeBrian Dolhansky
- Topics
- Music and Audio Processing (11 papers)Music Technology and Sound Studies (10 papers)Speech and Audio Processing (7 papers)
- Journals
- International Symposium/Conference on Music Information RetrievalDigital Collections - Ithaca College Library (Ithaca College)Zenodo (CERN European Organization for Nuclear Research)
- Partner nations
- United States
In The Last Decade
Jeffrey J. Scott
11 papers receiving 303 citations
Peers
Comparison fields: 5 of 34
- Signal Processing 286
- Computer Vision and Pattern Recognition 183
- Cognitive Neuroscience 126
- Artificial Intelligence 60
- Experimental and Cognitive Psychology 55
Countries citing papers authored by Jeffrey J. Scott
This map shows the geographic impact of Jeffrey J. Scott'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 Jeffrey J. Scott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey J. Scott more than expected).
Fields of papers citing papers by Jeffrey J. Scott
This network shows the impact of papers produced by Jeffrey J. Scott. 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 Jeffrey J. Scott. The network helps show where Jeffrey J. Scott may publish in the future.
Co-authorship network of co-authors of Jeffrey J. Scott
This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey J. Scott. A scholar is included among the top collaborators of Jeffrey J. Scott 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 Jeffrey J. Scott. Jeffrey J. Scott is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 7 | |
| 5 | 21 | |
| 6 | 10 | |
| 7 | 2 | |
| 8 | 12 | |
| 9 | Music emotion recognition: A state of the art review | 239 |
| 10 | 1 | |
| 11 | 33 | |
| 12 | 5 |
About Jeffrey J. Scott
Jeffrey J. Scott is a scholar working on Signal Processing, Architecture and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 345 indexed citations. Recurring topics across this work include Music and Audio Processing (11 papers), Music Technology and Sound Studies (10 papers) and Speech and Audio Processing (7 papers). The work is most often cited by research in Signal Processing (286 citations), Computer Vision and Pattern Recognition (183 citations) and Cognitive Neuroscience (126 citations). Jeffrey J. Scott has collaborated with scholars based in United States. Frequent co-authors include Youngmoo E. Kim, Erik M. Schmidt, Raymond Migneco, Brandon G. Morton, Patrick Richardson, Douglas Turnbull, Sang Won Lee and Brian Dolhansky. Their work appears in journals such as International Symposium/Conference on Music Information Retrieval, Digital Collections - Ithaca College Library (Ithaca College) and Zenodo (CERN European Organization for Nuclear Research).
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.