Amy N. Yates
- Computer Vision and Pattern Recognition top 5%
- Cognitive Neuroscience top 10%
- Experimental and Cognitive Psychology
- Signal Processing
- Social Psychology
- Co-authors
- P. Jonathon PhillipsYing HuAlice J. O’TooleCarina A. HahnDavid WhiteGéraldine JeckelnJacqueline G. CavazosRajeev Ranjan
- Topics
- Face recognition and analysis (6 papers)Face Recognition and Perception (3 papers)Face and Expression Recognition (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionCognitive NeuroscienceExperimental and Cognitive Psychology
- Partner nations
- United StatesAustraliaIsrael
In The Last Decade
Amy N. Yates
12 papers receiving 275 citations
Peers
Comparison fields: 5 of 73
- Computer Vision and Pattern Recognition 164
- Cognitive Neuroscience 121
- Experimental and Cognitive Psychology 51
- Signal Processing 41
- Social Psychology 40
Countries citing papers authored by Amy N. Yates
This map shows the geographic impact of Amy N. Yates'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 Amy N. Yates with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amy N. Yates more than expected).
Fields of papers citing papers by Amy N. Yates
This network shows the impact of papers produced by Amy N. Yates. 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 Amy N. Yates. The network helps show where Amy N. Yates may publish in the future.
Co-authorship network of co-authors of Amy N. Yates
This figure shows the co-authorship network connecting the top 25 collaborators of Amy N. Yates. A scholar is included among the top collaborators of Amy N. Yates 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 Amy N. Yates. Amy N. Yates 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 | 6 | |
| 3 | 7 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | Manipulation Data Collection and Annotation Tool for Media Forensics | 2 |
| 7 | 10 | |
| 8 | 2018 MediFor Challenge | 1 |
| 9 | 216 | |
| 10 | 9 | |
| 11 | 2 | |
| 12 | 13 | |
| 13 | 22 |
About Amy N. Yates
Amy N. Yates is a scholar working on Computer Vision and Pattern Recognition, Discrete Mathematics and Combinatorics and Biophysics, having authored 13 papers that have together received 291 indexed citations. Recurring topics across this work include Face recognition and analysis (6 papers), Face Recognition and Perception (3 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (164 citations), Cognitive Neuroscience (121 citations) and Experimental and Cognitive Psychology (51 citations). Amy N. Yates has collaborated with scholars based in United States, Australia and Israel. Frequent co-authors include P. Jonathon Phillips, Ying Hu, Alice J. O’Toole, Carina A. Hahn, David White, Géraldine Jeckeln, Jacqueline G. Cavazos, Rajeev Ranjan, Carlos D. Castillo and Jun-Cheng Chen. Their work appears in journals such as Proceedings of the National Academy of Sciences, Neurocomputing and Behavior Research Methods.
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.