arXiv:1612.01452 공식 코드 · Papers with Code

ImageNet pre-trained models with batch normalization

Marcel Simon, Erik Rodner, Joachim Denzler

제출 2016-12-05

원문 초록

Convolutional neural networks (CNN) pre-trained on ImageNet are the backbone of most state-of-the-art approaches. In this paper, we present a new set of pre-trained models with popular state-of-the-art architectures for the Caffe framework. The first release includes Residual Networks (ResNets) with generation script as well as the batch-normalization-variants of AlexNet and VGG19. All models outperform previous models with the same architecture. The models and training code are available at http://www.inf-cv.uni-jena.de/Research/CNN+Models.html and https://github.com/cvjena/cnn-models

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