Search Results for author: Michiaki Iwazume

Found 2 papers, 0 papers with code

Cavity Filling: Pseudo-Feature Generation for Multi-Class Imbalanced Data Problems in Deep Learning

no code implementations17 Jul 2018 Tomohiko Konno, Michiaki Iwazume

Herein, we generate pseudo-features based on the multivariate probability distributions obtained from the feature maps in layers of trained deep neural networks.

Icing on the Cake: An Easy and Quick Post-Learnig Method You Can Try After Deep Learning

no code implementations17 Jul 2018 Tomohiko Konno, Michiaki Iwazume

We found an easy and quick post-learning method named "Icing on the Cake" to enhance a classification performance in deep learning.

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