M. Ed Jernigan
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Atmospheric Science
- Co-authors
- David A. ClausiJohn A. RobinsonNeil D. B. BruceSusan J. LeatJavad AlirezaieClaude Nahmias
- Topics
- Advanced Image and Video Retrieval Techniques (2 papers)Advanced Vision and Imaging (2 papers)Medical Image Segmentation Techniques (2 papers)
- Cited by
- Media TechnologyComputer Vision and Pattern RecognitionIndustrial and Manufacturing Engineering
- Journals
- Pattern RecognitionInternational Journal of Pattern Recognition and Artificial IntelligenceProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
- Partner nations
- Canada
In The Last Decade
M. Ed Jernigan
6 papers receiving 230 citations
Peers
Comparison fields: 5 of 56
- Computer Vision and Pattern Recognition 175
- Media Technology 89
- Artificial Intelligence 45
- Radiology, Nuclear Medicine and Imaging 29
- Atmospheric Science 25
Countries citing papers authored by M. Ed Jernigan
This map shows the geographic impact of M. Ed Jernigan'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 M. Ed Jernigan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Ed Jernigan more than expected).
Fields of papers citing papers by M. Ed Jernigan
This network shows the impact of papers produced by M. Ed Jernigan. 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 M. Ed Jernigan. The network helps show where M. Ed Jernigan may publish in the future.
Co-authorship network of co-authors of M. Ed Jernigan
This figure shows the co-authorship network connecting the top 25 collaborators of M. Ed Jernigan. A scholar is included among the top collaborators of M. Ed Jernigan 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 M. Ed Jernigan. M. Ed Jernigan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 5 | |
| 3 | 246 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 6 |
About M. Ed Jernigan
M. Ed Jernigan is a scholar working on Computer Vision and Pattern Recognition, Sensory Systems and Neurology, having authored 6 papers that have together received 267 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (2 papers), Advanced Vision and Imaging (2 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Media Technology (89 citations), Computer Vision and Pattern Recognition (175 citations) and Industrial and Manufacturing Engineering (25 citations). M. Ed Jernigan has collaborated with scholars based in Canada. Frequent co-authors include David A. Clausi, John A. Robinson, Neil D. B. Bruce, Susan J. Leat, Javad Alirezaie and Claude Nahmias. Their work appears in journals such as Pattern Recognition, International Journal of Pattern Recognition and Artificial Intelligence and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.