Joseph P. Robinson
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Artificial Intelligence
- Genetics
- Archeology top 10%
- Topics
- Face recognition and analysis (17 papers)Generative Adversarial Networks and Image Synthesis (5 papers)Biometric Identification and Security (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingIEEE Transactions on Multimedia
- Partner nations
- United StatesMexicoChina
In The Last Decade
Joseph P. Robinson
22 papers receiving 362 citations
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 333
- Signal Processing 116
- Artificial Intelligence 31
- Genetics 30
- Archeology 26
Countries citing papers authored by Joseph P. Robinson
This map shows the geographic impact of Joseph P. Robinson'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 Joseph P. Robinson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joseph P. Robinson more than expected).
Fields of papers citing papers by Joseph P. Robinson
This network shows the impact of papers produced by Joseph P. Robinson. 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 Joseph P. Robinson. The network helps show where Joseph P. Robinson may publish in the future.
Co-authorship network of co-authors of Joseph P. Robinson
This figure shows the co-authorship network connecting the top 25 collaborators of Joseph P. Robinson. A scholar is included among the top collaborators of Joseph P. Robinson 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 Joseph P. Robinson. Joseph P. Robinson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 12 | |
| 3 | 3 | |
| 4 | 5 | |
| 5 | 4 | |
| 6 | 20 | |
| 7 | 10 | |
| 8 | Visual Kinship Recognition: A Decade in the Making | 2 |
| 9 | 47 | |
| 10 | 2 | |
| 11 | 14 | |
| 12 | 4 | |
| 13 | 16 | |
| 14 | 44 | |
| 15 | 4 | |
| 16 | 21 | |
| 17 | 39 | |
| 18 | 5 | |
| 19 | 4 | |
| 20 | 6 |
About Joseph P. Robinson
Joseph P. Robinson is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Signal Processing, having authored 22 papers that have together received 377 indexed citations. Recurring topics across this work include Face recognition and analysis (17 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Biometric Identification and Security (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (333 citations), Signal Processing (116 citations) and Human-Computer Interaction (21 citations). Joseph P. Robinson has collaborated with scholars based in United States, Mexico and China. Frequent co-authors include Yun Fu, Ming Shao, Yue Wu, Yu Yin, Hongfu Liu, Shuyang Wang, Yun Fu, Songyao Jiang, Yulun Zhang and Can Qin. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Multimedia.
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.