Bag of Tricks for Image Classification with Convolutional Neural Networks论文笔记
简介 当前许多图像分类的研究可以归功于训练过程的改进，例如改进数据增强和优化方法。然而在一些文献中，许多改进仅仅在实验细节中有简短的描述活在源码中才会出现。本文使用了这些小技巧将原始ResNet-50在ImageNet上的准确率从75.3%提升到79.29%。复现结果可以在GluonCV中找到，https://github.com/dmlc/gluon-cv。这篇文章可以看作是一群经验丰富的工程师
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相关文章
- 1. Bag of Tricks for Image Classification with Convolutional Neural Networks
- 2. 《Bag of Tricks for Image Classification with Convolutional Neural Networks》论文阅读笔记
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- 4. 论文解读-Bag of Tricks for Image Classification with Convolutional Neural Networks
- 5. 【论文阅读】Bag of Tricks for Image Classification with Convolutional Neural Networks
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