Chris Tensmeyer
Impact in
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- Handwritten Text Recognition Techniques
- Generative Adversarial Networks and Image Synthesis
- Multimodal Machine Learning Applications
- Image Processing and 3D Reconstruction
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
Papers in
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- Handwritten Text Recognition Techniques 8
- Image Processing and 3D Reconstruction 4
- Generative Adversarial Networks and Image Synthesis 4
- Image Retrieval and Classification Techniques 3
- Multimodal Machine Learning Applications 3
- Advanced Neural Network Applications 3
- Advanced Image and Video Retrieval Techniques 2
- Journals
- Pattern Recognition (1 paper)SN Computer Science (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesMexicoUnited Kingdom
In The Last Decade
Chris Tensmeyer
13 papers receiving 246 citations
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 205
- Computer Graphics and Computer-Aided Design 18
- Media Technology 32
- Artificial Intelligence 56
- Signal Processing 13
Countries citing papers authored by Chris Tensmeyer
This map shows the geographic impact of Chris Tensmeyer'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 Chris Tensmeyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Tensmeyer more than expected).
Fields of papers citing papers by Chris Tensmeyer
This network shows the impact of papers produced by Chris Tensmeyer. 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 Chris Tensmeyer. The network helps show where Chris Tensmeyer may publish in the future.
Co-authors
The 24 scholars most cited alongside Chris Tensmeyer, 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 | 2023 | 5 | |
| 2 | 2022 | 1 | |
| 3 | 2022 | 4 | |
| 4 | 2022 | 103 | |
| 5 | 2022 | 9 | |
| 6 | 2020 | 25 | |
| 7 | 2020 | 4 | |
| 8 | 2020 | 38 | |
| 9 | 2019 | 39 | |
| 10 | 2019 | 3 | |
| 11 | 2019 | 11 | |
| 12 | 2018 | 6 | |
| 13 | 2017 | 8 |
About Chris Tensmeyer
Chris Tensmeyer is a scholar working on Computer Vision and Pattern Recognition, General Social Sciences, Artificial Intelligence, Signal Processing and Infectious Diseases, having authored 13 papers that have together received 256 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (8 papers), Image Processing and 3D Reconstruction (4 papers), Generative Adversarial Networks and Image Synthesis (4 papers), Image Retrieval and Classification Techniques (3 papers), Multimodal Machine Learning Applications (3 papers), Advanced Neural Network Applications (3 papers), Topic Modeling (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (205 citations), Computer Graphics and Computer-Aided Design (18 citations), Media Technology (32 citations), Artificial Intelligence (56 citations) and Signal Processing (13 citations). Chris Tensmeyer has collaborated with scholars based in United States, Mexico and United Kingdom. Frequent co-authors include Tony Martinez, Tong Sun, Jiuxiang Gu, Tong Yu, Yufan Zhou, Ruiyi Zhang, Jinhui Xu, Changyou Chen, Curtis Wigington and Vlad I. Morariu. Their work appears in journals such as Pattern Recognition, SN Computer Science, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Proceedings of the AAAI Conference on Artificial 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.