Very Deep Convolutional Networks for Large-Scale Image Recognition
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Cites methods from "Very Deep Convolutional Networks fo..."
...We trained Networkin-Network [15] and VGG [25] for MNIST, CIFAR, SVHN, STL10, with minor adjustments for the corresponding image sizes....
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...VGG is another powerful network that proved to be useful in many applications beyond image classification, like object localization [23]....
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...For the ImageNet1000 dataset, we used pretrained VGG models from [5]....
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...All Caffe VGG models were converted to Torch models using the loadcaffe package [30]....
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...In particular in this paper, we consider the CIFAR10, MNIST, SVHN, STL10, and ImageNet1000 datasets, and two popular network architectures, Networkin-Network [15] and VGG [25]....
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