Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Frome, Andrea"'
Deep neural network pruning and quantization techniques have demonstrated it is possible to achieve high levels of compression with surprisingly little degradation to test set accuracy. However, this measure of performance conceals significant differ
Externí odkaz:
http://arxiv.org/abs/1911.05248
Viral diseases are major sources of poor yields for cassava, the 2nd largest provider of carbohydrates in Africa.At least 80% of small-holder farmer households in Sub-Saharan Africa grow cassava. Since many of these farmers have smart phones, they ca
Externí odkaz:
http://arxiv.org/abs/1908.02900
This paper presents experiments extending the work of Ba et al. (2014) on recurrent neural models for attention into less constrained visual environments, specifically fine-grained categorization on the Stanford Dogs data set. In this work we use an
Externí odkaz:
http://arxiv.org/abs/1412.7054
Autor:
Norouzi, Mohammad, Mikolov, Tomas, Bengio, Samy, Singer, Yoram, Shlens, Jonathon, Frome, Andrea, Corrado, Greg S., Dean, Jeffrey
Several recent publications have proposed methods for mapping images into continuous semantic embedding spaces. In some cases the embedding space is trained jointly with the image transformation. In other cases the semantic embedding space is establi
Externí odkaz:
http://arxiv.org/abs/1312.5650
Autor:
Deng, Jia, Ding, Nan, Jia, Yangqing, Frome, Andrea, Murphy, Kevin, Bengio, Samy, Li, Yuan, Neven, Hartmut, Adam, Hartwig
Publikováno v:
Computer Vision - ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I; 2014, p48-64, 17p
Publikováno v:
Advances in Neural Information Processing Systems 19; 2007, p417-424, 8p
Publikováno v:
2007 IEEE 11th International Conference on Computer Vision; 2007, p1-8, 8p
Autor:
Frome, Andrea, Malik, Jitendra
Publikováno v:
Nearest-Neighbor Methods in Learning & Vision; 2006, p222-247, 27p