Radford Juang
- Computer Networks and Communications top 5%
- Biomedical Engineering
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Artificial Intelligence
- Co-authors
- Tia GaoMatt WelshPhilippe BurlinaAndre LevchenkoBeatrice HoffmannDavid D. YuhElliot R. McVeighAmit Banerjee
- Topics
- Cardiac Valve Diseases and Treatments (2 papers)Remote-Sensing Image Classification (2 papers)Medical Image Segmentation Techniques (2 papers)
- Cited by
- Computer Networks and CommunicationsComputer Vision and Pattern RecognitionBiomedical Engineering
- Journals
- Ultrasound in Medicine & BiologyPubMedInternational Conference on Information Fusion
- Partner nations
- United States
In The Last Decade
Radford Juang
7 papers receiving 327 citations
Peers
Comparison fields: 5 of 70
- Computer Networks and Communications 191
- Biomedical Engineering 119
- Computer Vision and Pattern Recognition 102
- Electrical and Electronic Engineering 67
- Artificial Intelligence 58
Countries citing papers authored by Radford Juang
This map shows the geographic impact of Radford Juang'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 Radford Juang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Radford Juang more than expected).
Fields of papers citing papers by Radford Juang
This network shows the impact of papers produced by Radford Juang. 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 Radford Juang. The network helps show where Radford Juang may publish in the future.
Co-authorship network of co-authors of Radford Juang
This figure shows the co-authorship network connecting the top 25 collaborators of Radford Juang. A scholar is included among the top collaborators of Radford Juang 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 Radford Juang. Radford Juang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 15 | |
| 3 | 3 | |
| 4 | Comparative performance evaluation of GM-PHD filter in clutter | 10 |
| 5 | 30 | |
| 6 | 2 | |
| 7 | 287 |
About Radford Juang
Radford Juang is a scholar working on Media Technology, Biophysics and Computer Vision and Pattern Recognition, having authored 7 papers that have together received 349 indexed citations. Recurring topics across this work include Cardiac Valve Diseases and Treatments (2 papers), Remote-Sensing Image Classification (2 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Computer Networks and Communications (191 citations), Computer Vision and Pattern Recognition (102 citations) and Biomedical Engineering (119 citations). Radford Juang has collaborated with scholars based in United States. Frequent co-authors include Tia Gao, Matt Welsh, Philippe Burlina, Andre Levchenko, Beatrice Hoffmann, David D. Yuh, Elliot R. McVeigh, Amit Banerjee, Joshua Broadwater and C. Sprouse. Their work appears in journals such as Ultrasound in Medicine & Biology, PubMed and International Conference on Information Fusion.
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.