Karl Ricanek
- Computer Vision and Pattern Recognition top 0.5%
- Signal Processing top 1%
- Artificial Intelligence top 10%
- Dermatology top 5%
- Information Systems top 5%
- Co-authors
- Eric PattersonA. Midori AlbertGayathri MahalingamKhoa LuuChing Y. SuenTien D. BuiMichael C. KingYishi Wang
- Topics
- Face recognition and analysis (44 papers)Face and Expression Recognition (38 papers)Biometric Identification and Security (26 papers)
- Journals
- SHILAP Revista de lepidopterologíaComputerNeurocomputing
- Partner nations
- United StatesChinaCanada
In The Last Decade
Karl Ricanek
70 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Computer Vision and Pattern Recognition 1.5k
- Signal Processing 659
- Artificial Intelligence 156
- Dermatology 124
- Information Systems 117
Countries citing papers authored by Karl Ricanek
This map shows the geographic impact of Karl Ricanek'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 Karl Ricanek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karl Ricanek more than expected).
Fields of papers citing papers by Karl Ricanek
This network shows the impact of papers produced by Karl Ricanek. 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 Karl Ricanek. The network helps show where Karl Ricanek may publish in the future.
Co-authorship network of co-authors of Karl Ricanek
This figure shows the co-authorship network connecting the top 25 collaborators of Karl Ricanek. A scholar is included among the top collaborators of Karl Ricanek 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 Karl Ricanek. Karl Ricanek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 30 | |
| 5 | A Review of Face Recognition against Longitudinal Child Faces. | 21 |
| 6 | A Research Survey Application Using Eye Tracking Technology | 1 |
| 7 | 7 | |
| 8 | 30 | |
| 9 | 14 | |
| 10 | 9 | |
| 11 | Comparison of Genetic-based Feature Extraction Methods for Facial Recognition. | 9 |
| 12 | Genetic-Based Selection and Weighting for LBP, oLBP, and Eigenface Feature Extraction. | 3 |
| 13 | 18 | |
| 14 | 1 | |
| 15 | 14 | |
| 16 | 6 | |
| 17 | Using 3D Video Game Scenarios and Artificial Neural Networks to Classify Brain States for a Brain Computer Interface | 1 |
| 18 | 17 | |
| 19 | 223 | |
| 20 | 23 |
About Karl Ricanek
Karl Ricanek is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology, having authored 71 papers that have together received 1.9k indexed citations. Recurring topics across this work include Face recognition and analysis (44 papers), Face and Expression Recognition (38 papers) and Biometric Identification and Security (26 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Signal Processing (659 citations) and Dermatology (124 citations). Karl Ricanek has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Eric Patterson, A. Midori Albert, Gayathri Mahalingam, Khoa Luu, Ching Y. Suen, Tien D. Bui, Michael C. King, Yishi Wang, Cuixian Chen and Gerry Dozier. Their work appears in journals such as SHILAP Revista de lepidopterología, Computer and Neurocomputing.
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.