Ross Kindermann
Impact in
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- Medical Image Segmentation Techniques
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Image and Signal Denoising Methods
- Artificial Intelligence top 5%
- Bayesian Methods and Mixture Models
- Bayesian Modeling and Causal Inference
Papers in
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- Bayesian Methods and Mixture Models 3
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- Statistical Distribution Estimation and Applications 3
- Co-authors
- J. Laurie Snell (2 shared papers)V. N. LaRiccia (1 shared paper)Martin S. Levy (1 shared paper)
- Journals
- Journal of Mathematical Sociology (1 paper)The Annals of Probability (1 paper)Statistics & Probability Letters (1 paper)Communication in Statistics- Theory and Methods (2 papers)Contemporary mathematics - American Mathematical Society (1 paper)
- Partner nations
- United States
In The Last Decade
Ross Kindermann
6 papers receiving 769 citations
Ross Kindermann's Hit Papers
Peers
Comparison fields: 5 of 107
- Computer Vision and Pattern Recognition 220
- Artificial Intelligence 280
- Statistics and Probability 64
- Statistical and Nonlinear Physics 90
- Media Technology 57
Countries citing papers authored by Ross Kindermann
This map shows the geographic impact of Ross Kindermann'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 Ross Kindermann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ross Kindermann more than expected).
Fields of papers citing papers by Ross Kindermann
This network shows the impact of papers produced by Ross Kindermann. 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 Ross Kindermann. The network helps show where Ross Kindermann may publish in the future.
Co-authors
The 3 scholars most cited alongside Ross Kindermann, 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 | Markov Random Fields and Their Applications Hit paper breakdown → | 1980 | 799 |
| 2 | 1980 | 24 | |
| 3 | 1983 | 5 | |
| 4 | 1985 | 2 | |
| 5 | 1980 | 1 | |
| 6 | 1984 | 1 |
About Ross Kindermann
Ross Kindermann is a scholar working on Artificial Intelligence, Statistics and Probability, Mathematical Physics, Sociology and Political Science and Statistical and Nonlinear Physics, having authored 6 papers that have together received 832 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (3 papers), Bayesian Methods and Mixture Models (3 papers), Complex Network Analysis Techniques (1 paper), Hydrology and Drought Analysis (1 paper), Economic theories and models (1 paper), Stochastic processes and statistical mechanics (1 paper), Stochastic processes and financial applications (1 paper) and Evolutionary Game Theory and Cooperation (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (220 citations), Artificial Intelligence (280 citations), Statistics and Probability (64 citations), Statistical and Nonlinear Physics (90 citations) and Media Technology (57 citations). Ross Kindermann has collaborated with scholars based in United States. Frequent co-authors include J. Laurie Snell, V. N. LaRiccia and Martin S. Levy. Their work appears in journals such as Journal of Mathematical Sociology, The Annals of Probability, Statistics & Probability Letters, Communication in Statistics- Theory and Methods and Contemporary mathematics - American Mathematical Society.
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.