Victor DeBrunner
- Signal Processing top 1%
- Computational Mechanics top 2%
- Computer Vision and Pattern Recognition top 2%
- Electrical and Electronic Engineering
- Biomedical Engineering
- Co-authors
- Dayong ZhouLinda S. DeBrunnerTomasz PrzebindaMurad ÖzaydınValliappa LakshmananRobert M. RabinA.A. BeexJoseph Havlicek
- Topics
- Image and Signal Denoising Methods (54 papers)Advanced Adaptive Filtering Techniques (53 papers)Digital Filter Design and Implementation (44 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Information TheoryIEEE Transactions on Image Processing
- Partner nations
- United StatesChinaSweden
In The Last Decade
Victor DeBrunner
141 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 83
- Signal Processing 547
- Computational Mechanics 533
- Computer Vision and Pattern Recognition 370
- Electrical and Electronic Engineering 309
- Biomedical Engineering 177
Countries citing papers authored by Victor DeBrunner
This map shows the geographic impact of Victor DeBrunner'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 Victor DeBrunner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Victor DeBrunner more than expected).
Fields of papers citing papers by Victor DeBrunner
This network shows the impact of papers produced by Victor DeBrunner. 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 Victor DeBrunner. The network helps show where Victor DeBrunner may publish in the future.
Co-authorship network of co-authors of Victor DeBrunner
This figure shows the co-authorship network connecting the top 25 collaborators of Victor DeBrunner. A scholar is included among the top collaborators of Victor DeBrunner 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 Victor DeBrunner. Victor DeBrunner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 11 | |
| 7 | 7 | |
| 8 | Indirect Displacements Measurement Using Accelerometers and High-Resolution Signal Modeling | 2 |
| 9 | 0 | |
| 10 | 3 | |
| 11 | 138 | |
| 12 | 4 | |
| 13 | 13 | |
| 14 | 5 | |
| 15 | 1 | |
| 16 | 0 | |
| 17 | 3 | |
| 18 | 3 | |
| 19 | A hierarchical, multiscale texture segmentation algorithm for real-world scenes | 7 |
| 20 | 5 |
About Victor DeBrunner
Victor DeBrunner is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 160 papers that have together received 1.3k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (54 papers), Advanced Adaptive Filtering Techniques (53 papers) and Digital Filter Design and Implementation (44 papers). The work is most often cited by research in Signal Processing (547 citations), Computational Mechanics (533 citations) and Computer Vision and Pattern Recognition (370 citations). Victor DeBrunner has collaborated with scholars based in United States, China and Sweden. Frequent co-authors include Dayong Zhou, Linda S. DeBrunner, Tomasz Przebinda, Murad Özaydın, Valliappa Lakshmanan, Robert M. Rabin, A.A. Beex, Joseph Havlicek, Sebastián M. Torres and Minh C. Ta. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Information Theory and IEEE Transactions on Image Processing.
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.