Stephen W. Smoliar
- Computer Vision and Pattern Recognition top 0.2%
- Signal Processing top 0.2%
- Artificial Intelligence top 2%
- Sociology and Political Science top 2%
- Cognitive Neuroscience top 5%
- Co-authors
- Hao ZhangAtreyi KankanhalliAlbert S. BregmanRichard E. NisbettKeith J. HolyoakPaul ThagardJohn H. HollandJian Wu
- Topics
- Music Technology and Sound Studies (20 papers)Video Analysis and Summarization (19 papers)Music and Audio Processing (17 papers)
- Partner nations
- United StatesSingaporeIsrael
In The Last Decade
Stephen W. Smoliar
89 papers receiving 4.0k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Computer Vision and Pattern Recognition 2.7k
- Signal Processing 1.4k
- Artificial Intelligence 729
- Sociology and Political Science 592
- Cognitive Neuroscience 533
Countries citing papers authored by Stephen W. Smoliar
This map shows the geographic impact of Stephen W. Smoliar'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 Stephen W. Smoliar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen W. Smoliar more than expected).
Fields of papers citing papers by Stephen W. Smoliar
This network shows the impact of papers produced by Stephen W. Smoliar. 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 Stephen W. Smoliar. The network helps show where Stephen W. Smoliar may publish in the future.
Co-authorship network of co-authors of Stephen W. Smoliar
This figure shows the co-authorship network connecting the top 25 collaborators of Stephen W. Smoliar. A scholar is included among the top collaborators of Stephen W. Smoliar 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 Stephen W. Smoliar. Stephen W. Smoliar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | Toward Content-Based Audio Indexing and Retrieval and a New Speaker Discrimination Technique | 2 |
| 4 | 205 | |
| 5 | Contemplating Minds: A Forum for Artificial Intelligence | 9 |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 6 | |
| 9 | 71 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | The challenge of neural Darwinism | 1 |
| 13 | On making expert systems more like experts | 4 |
| 14 | Software Specifications, Data Bases and Knowledge Bases. | 0 |
| 15 | 11 | |
| 16 | An overview of ΦNIX | 3 |
| 17 | Systems Analysis and Design: A Foundation for the 1980's | 29 |
| 18 | 10 | |
| 19 | 105 | |
| 20 | 12 |
About Stephen W. Smoliar
Stephen W. Smoliar is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Music, having authored 100 papers that have together received 4.6k indexed citations. Recurring topics across this work include Music Technology and Sound Studies (20 papers), Video Analysis and Summarization (19 papers) and Music and Audio Processing (17 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.7k citations), Signal Processing (1.4k citations) and Cognitive Neuroscience (533 citations). Stephen W. Smoliar has collaborated with scholars based in United States, Singapore and Israel. Frequent co-authors include Hao Zhang, Atreyi Kankanhalli, Albert S. Bregman, Richard E. Nisbett, Keith J. Holyoak, Paul Thagard, John H. Holland, Jian Wu, Di Zhong and Douglas R. Hofstadter. Their work appears in journals such as Communications of the ACM, ACM Computing Surveys and Pattern Recognition.
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.