Bryan Usevitch

683 citations
21 papers · 456 · h-index 8

Impact in

    • Image and Signal Denoising Methods
    • Advanced Data Compression Techniques
    • Advanced Image Processing Techniques
    • Advanced Vision and Imaging
    • Digital Filter Design and Implementation
    • Video Coding and Compression Technologies
    • Blind Source Separation Techniques

Papers in

Bryan Usevitch

18 papers receiving 410 citations

Peers

Bryan Usevitch
Comparison fields: 5 of 52
  • Computer Vision and Pattern Recognition 375
  • Signal Processing 192
  • Media Technology 55
  • Computer Graphics and Computer-Aided Design 15
  • Hardware and Architecture 17
Replace Michael Gormish with:
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Citations per field
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Citations per year

Countries citing papers authored by Bryan Usevitch

Since Specialization
Citations

This map shows the geographic impact of Bryan Usevitch'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 Bryan Usevitch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bryan Usevitch more than expected).

Fields of papers citing papers by Bryan Usevitch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bryan Usevitch. 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 Bryan Usevitch. The network helps show where Bryan Usevitch may publish in the future.

Co-authors

The 10 scholars most cited alongside Bryan Usevitch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bryan Usevitch Line = papers co-authored together Bryan Usevitch links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001286
2 200260
3 199520
4 200320
5 199619
6 20068
7 20028
8 20078
9 19996
10 20055
11 20054
12 20053
13 20063
14
Perfect Reconstruction Filter Banks for Adaptive Filtering and Coding
19932
15 20031
16 20041
17 20021
18 20031
19 20060
20 20160

About Bryan Usevitch

Bryan Usevitch is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Computational Mechanics, Computational Theory and Mathematics and Electrical and Electronic Engineering, having authored 21 papers that have together received 456 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (17 papers), Advanced Data Compression Techniques (13 papers), Digital Filter Design and Implementation (12 papers), Image Retrieval and Classification Techniques (3 papers), Advanced Adaptive Filtering Techniques (2 papers), Wireless Communication Networks Research (1 paper), Advanced Optical Network Technologies (1 paper) and Optical Network Technologies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (375 citations), Signal Processing (192 citations), Media Technology (55 citations), Computer Graphics and Computer-Aided Design (15 citations) and Hardware and Architecture (17 citations). Bryan Usevitch has collaborated with scholars based in United States. Frequent co-authors include M.T. Orchard, Olga Kosheleva, E. Vidal, Sergio D. Cabrera, Apurva N. Mody, D. Lafaw, Vikram Jayaram, Mehdi Shadaram, W.K. Jenkins and Владик Крейнович. Their work appears in journals such as IEEE Signal Processing Magazine, IEEE Transactions on Image Processing, IEEE Transactions on Signal Processing, EURASIP Journal on Image and Video Processing and scholarworks - UTEP (The University of Texas at El Paso).

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.

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