Committees of Deep Feedforward Networks Trained with Few Data
نویسنده
چکیده
Deep convolutional neural networks are known to give good results on image classification tasks. In this paper we present a method to improve the classification result by combining multiple such networks in a committee. We adopt the STL-10 dataset which has very few training examples and show that our method can achieve results that are better than the state of the art. The networks are trained layer-wise and no backpropagation is used. We also explore the effects of dataset augmentation by mirroring, rotation, and scaling.
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ar X iv : 1 40 6 . 59 47 v 1 [ cs . C V ] 2 3 Ju n 20 14 Committees of deep feedforward networks trained with few data
Deep convolutional neural networks are known to give good results on image classification tasks. In this paper we present a method to improve the classification result by combining multiple such networks in a committee. We adopt the STL-10 dataset which has very few training examples and show that our method can achieve results that are better than the state of the art. The networks are trained...
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تاریخ انتشار 2014