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arxiv: 1312.5402 · v1 · submitted 2013-12-19 · 💻 cs.CV

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Some Improvements on Deep Convolutional Neural Network Based Image Classification

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classification 💻 cs.CV
keywords classificationimageaddingconvolutionaldatadeepnetworkneural
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We investigate multiple techniques to improve upon the current state of the art deep convolutional neural network based image classification pipeline. The techiques include adding more image transformations to training data, adding more transformations to generate additional predictions at test time and using complementary models applied to higher resolution images. This paper summarizes our entry in the Imagenet Large Scale Visual Recognition Challenge 2013. Our system achieved a top 5 classification error rate of 13.55% using no external data which is over a 20% relative improvement on the previous year's winner.

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  1. A Simple Framework for Contrastive Learning of Visual Representations

    cs.LG 2020-02 accept novelty 7.0

    SimCLR learns visual representations by contrasting augmented views of the same image and reaches 76.5% ImageNet top-1 accuracy with a linear classifier, matching a supervised ResNet-50.