Clark S. Lindsey
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition
- Nuclear and High Energy Physics
- Control and Systems Engineering
- Co-authors
- Thomas LindbladG. SzékelyTh. LindbladB. DenbyH. HaggertyMichael P. StrömbergMary Lou PadgettF. Block
- Topics
- Neural Networks and Applications (14 papers)Particle Detector Development and Performance (9 papers)Particle physics theoretical and experimental studies (7 papers)
- Journals
- Pattern Recognition LettersNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated EquipmentIEEE Transactions on Nuclear Science
- Partner nations
- SwedenUnited StatesNorway
In The Last Decade
Clark S. Lindsey
35 papers receiving 224 citations
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 120
- Electrical and Electronic Engineering 60
- Computer Vision and Pattern Recognition 40
- Nuclear and High Energy Physics 38
- Control and Systems Engineering 29
Countries citing papers authored by Clark S. Lindsey
This map shows the geographic impact of Clark S. Lindsey'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 Clark S. Lindsey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Clark S. Lindsey more than expected).
Fields of papers citing papers by Clark S. Lindsey
This network shows the impact of papers produced by Clark S. Lindsey. 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 Clark S. Lindsey. The network helps show where Clark S. Lindsey may publish in the future.
Co-authorship network of co-authors of Clark S. Lindsey
This figure shows the co-authorship network connecting the top 25 collaborators of Clark S. Lindsey. A scholar is included among the top collaborators of Clark S. Lindsey 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 Clark S. Lindsey. Clark S. Lindsey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 4 | |
| 10 | 6 | |
| 11 | 9 | |
| 12 | 7 | |
| 13 | 7 | |
| 14 | Review of hardware neural networks: A User's perspective | 38 |
| 15 | 9 | |
| 16 | 8 | |
| 17 | 4 | |
| 18 | 1 | |
| 19 | 14 | |
| 20 | 3 |
About Clark S. Lindsey
Clark S. Lindsey is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence and Radiation, having authored 38 papers that have together received 235 indexed citations. Recurring topics across this work include Neural Networks and Applications (14 papers), Particle Detector Development and Performance (9 papers) and Particle physics theoretical and experimental studies (7 papers). The work is most often cited by research in Artificial Intelligence (120 citations), Media Technology (27 citations) and Nuclear and High Energy Physics (38 citations). Clark S. Lindsey has collaborated with scholars based in Sweden, United States and Norway. Frequent co-authors include Thomas Lindblad, G. Székely, Th. Lindblad, B. Denby, H. Haggerty, Michael P. Strömberg, Mary Lou Padgett, F. Block, A. Jayakumar and G. Sekhniaidze. Their work appears in journals such as Pattern Recognition Letters, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and IEEE Transactions on Nuclear Science.
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.