Jason M. Kinser
- Media Technology top 1%
- Advanced Image Fusion Techniques 5
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- Image and Signal Denoising Methods 7
- Image Retrieval and Classification Techniques 5
- Artificial Intelligence top 5%
- Neural Networks and Applications 24
- Neural Networks and Reservoir Computing 7
- Biophysics top 5%
- Spectroscopy Techniques in Biomedical and Chemical Research 4
- Signal Processing top 10%
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- Neural dynamics and brain function 8
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- Spectroscopy and Chemometric Analyses 5
- Co-authors
- Thomas LindbladH. John CaulfieldSteven K. RogersJoseph ShamirAristide C. ChikandoNehal N. MehtaM. Saleet JafriAmit K. Dey
- Partner nations
- United StatesSwedenMauritius
In The Last Decade
Jason M. Kinser
60 papers receiving 802 citations
Peers
Comparison fields: 5 of 102
- Media Technology 314
- Computer Vision and Pattern Recognition 356
- Artificial Intelligence 284
- Biophysics 49
- Signal Processing 76
Countries citing papers authored by Jason M. Kinser
This map shows the geographic impact of Jason M. Kinser'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 Jason M. Kinser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason M. Kinser more than expected).
Fields of papers citing papers by Jason M. Kinser
This network shows the impact of papers produced by Jason M. Kinser. 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 Jason M. Kinser. The network helps show where Jason M. Kinser may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jason M. Kinser, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 1 | |
| 2 | 2022 | 0 | |
| 3 | 2021 | 14 | |
| 4 | Image Operators: Image Processing in Python | 2018 | 2 |
| 5 | 2015 | 2 | |
| 6 | VISUALIZING INSTANT MESSAGING AUTHOR WRITEPRINTS FOR FORENSIC ANALYSIS | 2014 | 3 |
| 7 | Python For Bioinformatics | 2008 | 11 |
| 8 | Inherent Features of Wavelets and Pulse Coupled Neural Networks | 2007 | 0 |
| 9 | 2004 | 40 | |
| 10 | 2000 | 0 | |
| 11 | 2000 | 0 | |
| 12 | 1999 | 45 | |
| 13 | 1999 | 27 | |
| 14 | 1999 | 7 | |
| 15 | 1999 | 48 | |
| 16 | 1999 | 22 | |
| 17 | Object Isolation Using a Pulse-Coupled Neural Network. | 1996 | 1 |
| 18 | 1996 | 1 | |
| 19 | 1996 | 3 | |
| 20 | 1988 | 14 |
About Jason M. Kinser
Jason M. Kinser is a scholar working on Media Technology, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 68 papers that have together received 866 indexed citations. Recurring topics across this work include Neural Networks and Applications (24 papers), Neural dynamics and brain function (8 papers), Image and Signal Denoising Methods (7 papers), Neural Networks and Reservoir Computing (7 papers), Advanced Image Fusion Techniques (5 papers), Image Retrieval and Classification Techniques (5 papers), Spectroscopy and Chemometric Analyses (5 papers) and Spectroscopy Techniques in Biomedical and Chemical Research (4 papers). The work is most often cited by research in Media Technology (314 citations), Computer Vision and Pattern Recognition (356 citations) and Artificial Intelligence (284 citations). Jason M. Kinser has collaborated with scholars based in United States, Sweden and Mauritius. Frequent co-authors include Thomas Lindblad, H. John Caulfield, Steven K. Rogers, Joseph Shamir, Aristide C. Chikando, Nehal N. Mehta, M. Saleet Jafri, Amit K. Dey, John W. Hickey and Guisong Wang. Their work appears in journals such as PLoS ONE, Proceedings of the IEEE and Optics Letters.
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.