119 citations · 166 across the 13 of their papers we have counts for
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cs.CV2017
OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning
José Lezama, Qiang Qiu, Pablo Musé +1
Deep neural networks trained using a softmax layer at the top and the cross-entropy loss are ubiquitous tools for image classification. Yet, this does not naturally enforce intra-c…
cs.CV2017
ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks
Qiang Qiu, Jose Lezama, Alex Bronstein +1
Hash codes are efficient data representations for coping with the ever growing amounts of data. In this paper, we introduce a random forest semantic hashing scheme that embeds tiny…