Nicolas Pinto

3.5k citations
18 papers · 1.9k · 1 hit paper · h-index 13

Impact in

    • Face and Expression Recognition
    • Face recognition and analysis
    • Advanced Image and Video Retrieval Techniques
    • Visual Attention and Saliency Detection
    • Neural dynamics and brain function
    • Visual perception and processing mechanisms
    • Face Recognition and Perception

Papers in

Nicolas Pinto

18 papers receiving 1.9k citations

Nicolas Pinto's Hit Papers

PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation 2011 · 356 citations
3560+5+10Years since publication100200300

Peers

Nicolas Pinto
Comparison fields: 5 of 132
  • Computer Vision and Pattern Recognition 883
  • Cognitive Neuroscience 522
  • Hardware and Architecture 152
  • Signal Processing 170
  • Artificial Intelligence 445
Replace Jeffrey Mark Siskind with:
Jeffrey Mark Siskind United States
Pascal Lamblin Canada
Philip H. W. Leong Australia
Joseph F. Murray United States
Hans Peter Graf United States
Eduard Säckinger United States
Li Deng China
John C. Hart United States
Raghuveer Rao United States
Á. Rodríguez‐Vázquez Spain
Nicolas Pinto relative to Jeffrey Mark Siskind United States Jeffrey Mark Siskind's profile →
Citations per field
00.5×2.6×
Jeffrey Mark Siskind · 1×
Citations per year

Countries citing papers authored by Nicolas Pinto

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

The 21 scholars most cited alongside Nicolas Pinto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nicolas Pinto Line = papers co-authored together Nicolas Pinto links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2014397
2 2008359
3
PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation
Hit paper breakdown →
2011356
4 2009162
5 2009135
6 2011132
7 201178
8 201374
9
PyCUDA: GPU Run-Time Code Generation for High-Performance Computing
200954
10 201147
11 201242
12
Establishing Good Benchmarks and Baselines for Face Recognition
200832
13 201426
14 20099
15 20127
16 20122
17 20151
18 20141

About Nicolas Pinto

Nicolas Pinto is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, Hardware and Architecture and Computer Networks and Communications, 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), Face recognition and analysis (6 papers), Visual perception and processing mechanisms (3 papers), Parallel Computing and Optimization Techniques (3 papers), Face Recognition and Perception (2 papers), Embedded Systems Design Techniques (2 papers) and Neural dynamics and brain function (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (883 citations), Cognitive Neuroscience (522 citations), Hardware and Architecture (152 citations), Signal Processing (170 citations) and Artificial Intelligence (445 citations). Nicolas Pinto has collaborated with scholars based in United States, Canada and Brazil. Frequent co-authors include David Cox, James J. DiCarlo, Andreas Klöckner, Yunsup Lee, Ahmed R. Fasih, Bryan Catanzaro, Paul Ivanov, Najib J. Majaj, Daniel Yamins and Charles F. Cadieu. Their work appears in journals such as PLoS Computational Biology, Image and Vision Computing, Parallel Computing, IEEE Transactions on Information Forensics and Security and Digital Access to Scholarship at Harvard (DASH) (Harvard University).

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.

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