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Disambiguation of "Pinto, Nicolas"

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PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation

, , , , , and . Parallel Computing, 38 (3): 157--174 (March 2012)
DOI: 10.1016/j.parco.2011.09.001

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Sonia Maria Pinto Escoval

Elizabeth Pinto

Mariano Aurelio Ernesto Pinto-Bazurco Mendieta

Sofia Pinto

Christian Pinto

 

Other publications of authors with the same name

The Neural Representation Benchmark and its Evaluation on Brain and Machine, , , , , and . ICLR, (2013)PyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation, , , , , and . Parallel Computing, 38 (3): 157--174 (March 2012)How far can you get with a modern face recognition test set using only simple features?., , and . CVPR, page 2591-2598. IEEE Computer Society, (2009)High-throughput-derived biologically-inspired features for unconstrained face recognition., and . Image Vis. Comput., 30 (3): 159-168 (2012)Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition., , , , , , , and . PLoS Comput. Biol., (2014)Comparing state-of-the-art visual features on invariant object recognition tasks., , , and . WACV, page 463-470. IEEE Computer Society, (2011)HEAR 2021: Holistic Evaluation of Audio Representations., , , , , , , , , and 13 other author(s). CoRR, (2022)SkData: Data Sets and Algorithm Evaluation Protocols in Python., , and . SciPy, page 20-26. scipy.org, (2013)Why is Real-World Visual Object Recognition Hard?, , and . PLoS Comput. Biol., (2008)An Evaluation of the Invariance Properties of a Biologically-Inspired System for Unconstrained Face Recognition., and . BIONETICS, volume 87 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 505-518. Springer, (2010)