Cristian Canton Ferrer
- Computer Vision and Pattern Recognition top 10%
- Experimental and Cognitive Psychology top 10%
- Artificial Intelligence
- Signal Processing
- Cognitive Neuroscience
- Co-authors
- Emad BarsoumCha ZhangSarah Adel BargalCaner HazırbaşAlbert GordoVikash SehwagJoanna BittonBrian Dolhansky
- Topics
- Generative Adversarial Networks and Image Synthesis (3 papers)Adversarial Robustness in Machine Learning (3 papers)Ethics and Social Impacts of AI (3 papers)
- Cited by
- Experimental and Cognitive PsychologyComputer Vision and Pattern RecognitionHealth Informatics
- Journals
- Nature Machine Intelligence2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- United StatesIndiaIsrael
In The Last Decade
Cristian Canton Ferrer
11 papers receiving 188 citations
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 125
- Experimental and Cognitive Psychology 88
- Artificial Intelligence 55
- Signal Processing 22
- Cognitive Neuroscience 21
Countries citing papers authored by Cristian Canton Ferrer
This map shows the geographic impact of Cristian Canton Ferrer'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 Cristian Canton Ferrer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cristian Canton Ferrer more than expected).
Fields of papers citing papers by Cristian Canton Ferrer
This network shows the impact of papers produced by Cristian Canton Ferrer. 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 Cristian Canton Ferrer. The network helps show where Cristian Canton Ferrer may publish in the future.
Co-authorship network of co-authors of Cristian Canton Ferrer
This figure shows the co-authorship network connecting the top 25 collaborators of Cristian Canton Ferrer. A scholar is included among the top collaborators of Cristian Canton Ferrer 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 Cristian Canton Ferrer. Cristian Canton Ferrer 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 | 1 | |
| 3 | 11 | |
| 4 | 3 | |
| 5 | 24 | |
| 6 | 3 | |
| 7 | 16 | |
| 8 | 8 | |
| 9 | 109 | |
| 10 | 3D human action recognition in multiple view scenarios | 3 |
| 11 | Texture and edge adaptive weak Matching Pursuit | 2 |
About Cristian Canton Ferrer
Cristian Canton Ferrer is a scholar working on Health Informatics, Computer Vision and Pattern Recognition and Safety Research, having authored 11 papers that have together received 193 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (3 papers), Adversarial Robustness in Machine Learning (3 papers) and Ethics and Social Impacts of AI (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (88 citations), Computer Vision and Pattern Recognition (125 citations) and Health Informatics (4 citations). Cristian Canton Ferrer has collaborated with scholars based in United States, India and Israel. Frequent co-authors include Emad Barsoum, Cha Zhang, Sarah Adel Bargal, Caner Hazırbaş, Albert Gordo, Vikash Sehwag, Joanna Bitton, Brian Dolhansky, Tal Hassner and Ivan Evtimov. Their work appears in journals such as Nature Machine Intelligence and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.