Kevin L. Priddy
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Civil and Structural Engineering top 10%
- Mechanical Engineering
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Paul E. KellerEmre ErtinSteven K. RogersDennis W. RuckMatthew KabriskyR. SaeksCheng‐Di DongYuanwei Jin
- Topics
- Neural Networks and Applications (8 papers)Fault Detection and Control Systems (3 papers)Indoor and Outdoor Localization Technologies (2 papers)
- Cited by
- Artificial IntelligenceCivil and Structural EngineeringComputer Vision and Pattern Recognition
- Journals
- NeurocomputingSPIE eBooksDefense Technical Information Center (DTIC)
- Partner nations
- United StatesChina
In The Last Decade
Kevin L. Priddy
22 papers receiving 611 citations
Peers
Comparison fields: 5 of 142
- Artificial Intelligence 160
- Electrical and Electronic Engineering 99
- Civil and Structural Engineering 91
- Mechanical Engineering 76
- Computer Vision and Pattern Recognition 69
Countries citing papers authored by Kevin L. Priddy
This map shows the geographic impact of Kevin L. Priddy'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 Kevin L. Priddy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin L. Priddy more than expected).
Fields of papers citing papers by Kevin L. Priddy
This network shows the impact of papers produced by Kevin L. Priddy. 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 Kevin L. Priddy. The network helps show where Kevin L. Priddy may publish in the future.
Co-authorship network of co-authors of Kevin L. Priddy
This figure shows the co-authorship network connecting the top 25 collaborators of Kevin L. Priddy. A scholar is included among the top collaborators of Kevin L. Priddy 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 Kevin L. Priddy. Kevin L. Priddy 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 | 4 | |
| 3 | 8 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | Evolutionary and Bio-inspired Computation: Theory and Applications III | 2 |
| 7 | 2 | |
| 8 | Intelligent Computing: Theory and Applications IV | 0 |
| 9 | 471 | |
| 10 | Artificial Neural Networks: An Introduction (SPIE Tutorial Texts in Optical Engineering, Vol. TT68) | 57 |
| 11 | 13 | |
| 12 | 4 | |
| 13 | Intelligent Computing: Theory And Applications III | 2 |
| 14 | Intelligent Computing: Theory and Applications V | 1 |
| 15 | 3 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 14 | |
| 19 | 3 | |
| 20 | 42 |
About Kevin L. Priddy
Kevin L. Priddy is a scholar working on Instrumentation, Artificial Intelligence and Media Technology, having authored 24 papers that have together received 648 indexed citations. Recurring topics across this work include Neural Networks and Applications (8 papers), Fault Detection and Control Systems (3 papers) and Indoor and Outdoor Localization Technologies (2 papers). The work is most often cited by research in Artificial Intelligence (160 citations), Civil and Structural Engineering (91 citations) and Computer Vision and Pattern Recognition (69 citations). Kevin L. Priddy has collaborated with scholars based in United States and China. Frequent co-authors include Paul E. Keller, Emre Ertin, Steven K. Rogers, Dennis W. Ruck, Matthew Kabrisky, R. Saeks, Cheng‐Di Dong, Yuanwei Jin, William E. Pierson and T.H. O'Donnell. Their work appears in journals such as Neurocomputing, SPIE eBooks and Defense Technical Information Center (DTIC).
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.