Connor J. Parde
Impact in
- Cognitive Neuroscience top 10%
- Face Recognition and Perception
- Psychology of Moral and Emotional Judgment
-
- Evolutionary Psychology and Human Behavior
Papers in
-
- Face recognition and analysis 10
- Face and Expression Recognition 4
- Generative Adversarial Networks and Image Synthesis 1
-
- Face Recognition and Perception 7
- Aesthetic Perception and Analysis 1
- Co-authors
- Alice J. O’Toole (11 shared papers)Matthew Q. Hill (8 shared papers)Carlos D. Castillo (10 shared papers)Rama Chellappa (1 shared paper)Ying Hu (3 shared papers)Naureen Mahmood (1 shared paper)Volker Blanz (2 shared papers)Rajeev Ranjan (2 shared papers)
- Journals
- Journal of Vision (4 papers)ACM Transactions on Applied Perception (2 papers)Nature Machine Intelligence (1 paper)Trends in Cognitive Sciences (1 paper)Cognition (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Connor J. Parde
10 papers receiving 223 citations
Peers
Comparison fields: 5 of 61
- Cognitive Neuroscience 133
- Experimental and Cognitive Psychology 88
- Computer Vision and Pattern Recognition 129
- Signal Processing 19
- Pharmacy 7
Countries citing papers authored by Connor J. Parde
This map shows the geographic impact of Connor J. Parde'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 Connor J. Parde with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Connor J. Parde more than expected).
Fields of papers citing papers by Connor J. Parde
This network shows the impact of papers produced by Connor J. Parde. 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 Connor J. Parde. The network helps show where Connor J. Parde may publish in the future.
Co-authors
The 14 scholars most cited alongside Connor J. Parde, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 96 | |
| 2 | 2019 | 47 | |
| 3 | 2018 | 43 | |
| 4 | 2019 | 19 | |
| 5 | 2021 | 12 | |
| 6 | 2021 | 10 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 1 | |
| 9 | 2019 | 1 | |
| 10 | 2018 | 1 | |
| 11 | 2017 | 0 |
About Connor J. Parde
Connor J. Parde is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience, Experimental and Cognitive Psychology, Museology and Signal Processing, having authored 11 papers that have together received 232 indexed citations. Recurring topics across this work include Face recognition and analysis (10 papers), Face Recognition and Perception (7 papers), Evolutionary Psychology and Human Behavior (5 papers), Face and Expression Recognition (4 papers), Fashion and Cultural Textiles (1 paper), Biometric Identification and Security (1 paper), Aesthetic Perception and Analysis (1 paper) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Cognitive Neuroscience (133 citations), Experimental and Cognitive Psychology (88 citations), Computer Vision and Pattern Recognition (129 citations), Signal Processing (19 citations) and Pharmacy (7 citations). Connor J. Parde has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Alice J. O’Toole, Matthew Q. Hill, Carlos D. Castillo, Rama Chellappa, Ying Hu, Naureen Mahmood, Volker Blanz, Rajeev Ranjan, Jun-Cheng Chen and Swami Sankaranarayanan. Their work appears in journals such as Journal of Vision, ACM Transactions on Applied Perception, Nature Machine Intelligence, Trends in Cognitive Sciences and Cognition.
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.