Christopher M. Brown
- Computer Vision and Pattern Recognition top 0.2%
- Biomedical Engineering top 5%
- Aerospace Engineering top 1%
- Molecular Biology top 10%
- Electrical and Electronic Engineering top 10%
- Co-authors
- Dana H. BallardJoachim DenzlerDouglas A. CampbellDavid R. RiveraChris XuDimitre G. OuzounovWatt W. WebbJoseph Wang
- Topics
- Veterinary Equine Medical Research (17 papers)Marine and coastal ecosystems (11 papers)Robotics and Sensor-Based Localization (10 papers)
- Journals
- Proceedings of the National Academy of SciencesNucleic Acids ResearchIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Christopher M. Brown
125 papers receiving 7.0k citations
Hit Papers
Peers
Comparison fields: 5 of 211
- Computer Vision and Pattern Recognition 2.9k
- Biomedical Engineering 966
- Aerospace Engineering 867
- Molecular Biology 735
- Electrical and Electronic Engineering 563
Countries citing papers authored by Christopher M. Brown
This map shows the geographic impact of Christopher M. Brown'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 Christopher M. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher M. Brown more than expected).
Fields of papers citing papers by Christopher M. Brown
This network shows the impact of papers produced by Christopher M. Brown. 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 Christopher M. Brown. The network helps show where Christopher M. Brown may publish in the future.
Co-authorship network of co-authors of Christopher M. Brown
This figure shows the co-authorship network connecting the top 25 collaborators of Christopher M. Brown. A scholar is included among the top collaborators of Christopher M. Brown 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 Christopher M. Brown. Christopher M. Brown is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 12 | |
| 3 | 87 | |
| 4 | 105 | |
| 5 | 20 | |
| 6 | 32 | |
| 7 | 28 | |
| 8 | 33 | |
| 9 | 1 | |
| 10 | 70 | |
| 11 | 28 | |
| 12 | 28 | |
| 13 | 10 | |
| 14 | 33 | |
| 15 | 19 | |
| 16 | 23 | |
| 17 | 16 | |
| 18 | 118 | |
| 19 | 2 | |
| 20 | Representing the Orientation of Dendritic Fields with Geodesic Tesselations, | 4 |
About Christopher M. Brown
Christopher M. Brown is a scholar working on Equine, Small Animals and Human-Computer Interaction, having authored 127 papers that have together received 7.6k indexed citations. Recurring topics across this work include Veterinary Equine Medical Research (17 papers), Marine and coastal ecosystems (11 papers) and Robotics and Sensor-Based Localization (10 papers). The work is most often cited by research in Equine (335 citations), Computer Vision and Pattern Recognition (2.9k citations) and Computer Graphics and Computer-Aided Design (229 citations). Christopher M. Brown has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Dana H. Ballard, Joachim Denzler, Douglas A. Campbell, David R. Rivera, Chris Xu, Dimitre G. Ouzounov, Watt W. Webb, Joseph Wang, David Coombs and Kay D. Bidle. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.