Lisa Gottesfeld Brown
- Computer Vision and Pattern Recognition top 0.5%
- Aerospace Engineering top 1%
- Media Technology top 0.5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 10%
- Topics
- Advanced Image and Video Retrieval Techniques (4 papers)Image Retrieval and Classification Techniques (2 papers)Advanced Vision and Imaging (2 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceACM Computing SurveysProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
- Partner nations
- United States
In The Last Decade
Lisa Gottesfeld Brown
5 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Computer Vision and Pattern Recognition 2.4k
- Aerospace Engineering 895
- Media Technology 474
- Radiology, Nuclear Medicine and Imaging 318
- Artificial Intelligence 191
Countries citing papers authored by Lisa Gottesfeld Brown
This map shows the geographic impact of Lisa Gottesfeld 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 Lisa Gottesfeld Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lisa Gottesfeld Brown more than expected).
Fields of papers citing papers by Lisa Gottesfeld Brown
This network shows the impact of papers produced by Lisa Gottesfeld 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 Lisa Gottesfeld Brown. The network helps show where Lisa Gottesfeld Brown may publish in the future.
Co-authorship network of co-authors of Lisa Gottesfeld Brown
This figure shows the co-authorship network connecting the top 25 collaborators of Lisa Gottesfeld Brown. A scholar is included among the top collaborators of Lisa Gottesfeld 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 Lisa Gottesfeld Brown. Lisa Gottesfeld 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 | 1 | |
| 2 | 100 | |
| 3 | 4 | |
| 4 | A survey of image registration techniquesbreakdown → | 2832 |
| 5 | 59 |
About Lisa Gottesfeld Brown
Lisa Gottesfeld Brown is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 5 papers that have together received 3.0k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Image Retrieval and Classification Techniques (2 papers) and Advanced Vision and Imaging (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.4k citations), Media Technology (474 citations) and Aerospace Engineering (895 citations). Lisa Gottesfeld Brown has collaborated with scholars based in United States. Frequent co-authors include Terrance E. Boult, Marilyn E. Noz and Gerald Q. Maguire. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Computing Surveys and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.