Nicolas Pinto
Nicolas Pinto
Research Scientist at MIT and Harvard, Lecturer at Harvard
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Why is real-world visual object recognition hard?
N Pinto, DD Cox, JJ DiCarlo
PLoS computational biology 4 (1), e27, 2008
PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation
A Klöckner, N Pinto, Y Lee, B Catanzaro, P Ivanov, A Fasih
Parallel Computing, 2011
Deep neural networks rival the representation of primate IT cortex for core visual object recognition
CF Cadieu, H Hong, DLK Yamins, N Pinto, D Ardila, EA Solomon, ...
PLoS computational biology 10 (12), e1003963, 2014
A high-throughput screening approach to discovering good forms of biologically inspired visual representation
N Pinto, D Doukhan, JJ DiCarlo, DD Cox
PLoS computational biology 5 (11), e1000579, 2009
Beyond simple features: A large-scale feature search approach to unconstrained face recognition
N Pinto, DD Cox
IEEE Automated Face and Gesture Recognition (FG) 25, 26-27, 2011
How far can you get with a modern face recognition test set using only simple features?
N Pinto, JJ DiCarlo, DD Cox
Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on …, 2009
Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook
N Pinto, Z Stone, T Zickler, D Cox
CVPR 2011 WORKSHOPS, 35-42, 2011
Experience grounds language
Y Bisk, A Holtzman, J Thomason, J Andreas, Y Bengio, J Chai, M Lapata, ...
arXiv preprint arXiv:2004.10151, 2020
Machine learning for predictive auto-tuning with boosted regression trees
J Bergstra, N Pinto, D Cox
2012 Innovative Parallel Computing (InPar), 1-9, 2012
Comparing state-of-the-art visual features on invariant object recognition tasks
N Pinto, Y Barhomi, DD Cox, JJ DiCarlo
2011 IEEE workshop on Applications of computer vision (WACV), 463-470, 2011
Establishing good benchmarks and baselines for face recognition
N Pinto, JJ DiCarlo, DD Cox
Workshop on Faces In'Real-Life'Images: Detection, Alignment, and Recognition, 2008
The 2013 face recognition evaluation in mobile environment
M Günther, A Costa-Pazo, C Ding, E Boutellaa, G Chiachia, H Zhang, ...
2013 International Conference on Biometrics (ICB), 1-7, 2013
Learning person-specific representations from faces in the wild
G Chiachia, AX Falcao, N Pinto, A Rocha, D Cox
IEEE Transactions on Information Forensics and Security 9 (12), 2089-2099, 2014
The neural representation benchmark and its evaluation on brain and machine
CF Cadieu, H Hong, D Yamins, N Pinto, NJ Majaj, JJ DiCarlo
arXiv preprint arXiv:1301.3530, 2013
Person-Specific Subspace Analysis for Unconstrained Familiar Face Identification.
G Chiachia, N Pinto, WR Schwartz, A Rocha, AX Falcão, DD Cox
BMVC, 1-12, 2012
Human versus machine: comparing visual object recognition systems on a level playing field
N Pinto, N Majaj, Y Barhomi, E Solomon, JJ DiCarlo
Cosyne Abstracts, 2010
An evaluation of the invariance properties of a biologically-inspired system for unconstrained face recognition
N Pinto, D Cox
International Conference on Bio-Inspired Models of Network, Information, and …, 2010
PyCUDA: GPU Run-Time code generation for High
A Klöckner, N Pinto, Y Lee, B Catanzaro, P Ivanov, A Fasih
Performance computing, 2009
GPU scripting and code generation with PyCUDA
A Klöckner, N Pinto, B Catanzaro, Y Lee, P Ivanov, A Fasih
GPU Computing Gems Jade Edition, 373-385, 2012
High-throughput-derived biologically-inspired features for unconstrained face recognition
N Pinto, DD Cox
Image and Vision Computing 30 (3), 159-168, 2012
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