Ronald L. Allen
- Artificial Intelligence
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Biomedical Engineering
- Control and Systems Engineering
- Co-authors
- Duncan W. MillsKien NguyenAnil K. JainErnest M. StokelyFarhad KamangarMike WhelanW. M. DuncanG. B. Stephenson
- Topics
- Image and Signal Denoising Methods (3 papers)Medical Image Segmentation Techniques (3 papers)Neural Networks and Applications (2 papers)
- Journals
- IEEE Transactions on Signal ProcessingJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and PhenomenaCERN Document Server (European Organization for Nuclear Research)
- Partner nations
- United States
In The Last Decade
Ronald L. Allen
9 papers receiving 264 citations
Peers
Comparison fields: 5 of 81
- Artificial Intelligence 71
- Computer Vision and Pattern Recognition 64
- Electrical and Electronic Engineering 46
- Biomedical Engineering 40
- Control and Systems Engineering 38
Countries citing papers authored by Ronald L. Allen
This map shows the geographic impact of Ronald L. Allen'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 Ronald L. Allen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ronald L. Allen more than expected).
Fields of papers citing papers by Ronald L. Allen
This network shows the impact of papers produced by Ronald L. Allen. 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 Ronald L. Allen. The network helps show where Ronald L. Allen may publish in the future.
Co-authorship network of co-authors of Ronald L. Allen
This figure shows the co-authorship network connecting the top 25 collaborators of Ronald L. Allen. A scholar is included among the top collaborators of Ronald L. Allen 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 Ronald L. Allen. Ronald L. Allen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 47 | |
| 2 | 33 | |
| 3 | Signal analysis | 12 |
| 4 | Signal Analysis: Time, Frequency, Scale and Structure | 158 |
| 5 | 7 | |
| 6 | 9 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 22 | |
| 10 | Motion analysis using orthogonal wavelets in the spatio-temporal filtering paradigm | 0 |
About Ronald L. Allen
Ronald L. Allen is a scholar working on Computer Vision and Pattern Recognition, Surfaces, Coatings and Films and Industrial and Manufacturing Engineering, having authored 10 papers that have together received 293 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (3 papers), Medical Image Segmentation Techniques (3 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Signal Processing (34 citations), Computer Vision and Pattern Recognition (64 citations) and Health Informatics (3 citations). Ronald L. Allen has collaborated with scholars based in United States. Frequent co-authors include Duncan W. Mills, Kien Nguyen, Anil K. Jain, Ernest M. Stokely, Farhad Kamangar, Mike Whelan, W. M. Duncan and G. B. Stephenson. Their work appears in journals such as IEEE Transactions on Signal Processing, Journal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and Phenomena and CERN Document Server (European Organization for Nuclear Research).
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.