Nicolas Pinto
- Computer Vision and Pattern Recognition top 1%
- Cognitive Neuroscience top 5%
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Electrical and Electronic Engineering
- Co-authors
- David CoxJames J. DiCarloAndreas KlöcknerPaul IvanovBryan CatanzaroAhmed R. FasihYunsup LeeDaniel Yamins
- Topics
- Face and Expression Recognition (8 papers)Advanced Image and Video Retrieval Techniques (6 papers)Face recognition and analysis (6 papers)
- Journals
- PLoS Computational BiologyIEEE Transactions on Information Forensics and SecurityImage and Vision Computing
- Partner nations
- United StatesBrazilCanada
In The Last Decade
Nicolas Pinto
18 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Computer Vision and Pattern Recognition 885
- Cognitive Neuroscience 522
- Artificial Intelligence 449
- Signal Processing 170
- Electrical and Electronic Engineering 170
Countries citing papers authored by Nicolas Pinto
This map shows the geographic impact of Nicolas Pinto'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 Nicolas Pinto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicolas Pinto more than expected).
Fields of papers citing papers by Nicolas Pinto
This network shows the impact of papers produced by Nicolas Pinto. 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 Nicolas Pinto. The network helps show where Nicolas Pinto may publish in the future.
Co-authorship network of co-authors of Nicolas Pinto
This figure shows the co-authorship network connecting the top 25 collaborators of Nicolas Pinto. A scholar is included among the top collaborators of Nicolas Pinto 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 Nicolas Pinto. Nicolas Pinto 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 | Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognitionbreakdown → | 391 |
| 3 | 26 | |
| 4 | 1 | |
| 5 | 73 | |
| 6 | 41 | |
| 7 | 7 | |
| 8 | 2 | |
| 9 | 132 | |
| 10 | 47 | |
| 11 | 77 | |
| 12 | PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generationbreakdown → | 352 |
| 13 | 162 | |
| 14 | PyCUDA: GPU Run-Time Code Generation for High-Performance Computing | 53 |
| 15 | 135 | |
| 16 | 9 | |
| 17 | 359 | |
| 18 | Establishing Good Benchmarks and Baselines for Face Recognition | 32 |
About Nicolas Pinto
Nicolas Pinto is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Biophysics, having authored 18 papers that have together received 1.9k indexed citations. Recurring topics across this work include Face and Expression Recognition (8 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Face recognition and analysis (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (885 citations), Cognitive Neuroscience (522 citations) and Hardware and Architecture (151 citations). Nicolas Pinto has collaborated with scholars based in United States, Brazil and Canada. Frequent co-authors include David Cox, James J. DiCarlo, Andreas Klöckner, Paul Ivanov, Bryan Catanzaro, Ahmed R. Fasih, Yunsup Lee, Daniel Yamins, Ethan A. Solomon and Ha Hong. Their work appears in journals such as PLoS Computational Biology, IEEE Transactions on Information Forensics and Security and Image and Vision Computing.
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.