Self-training with Noisy Student improves ImageNet classification阅读笔记

时间 2021-01-02

标签算法 classfication 论文阅读繁體版

原文原文链接

论文地址：https://arxiv.org/pdf/1911.04252v1.pdf 这篇文章实现了自训练方法，使用部分带标签数据进行训练，在ImageNet上top-1为87.4%。方法： 1. 为有标签和无标签的图片。 2. 使用有标签的数据、标准交叉熵损失训练了一个EfficientNet作为教师网络。 3. 用这个教师网络，在无标签数据上生成伪标签，伪标签可以是soft label(持

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1. Self-training with Noisy Student improves ImageNet classification论文解析
2. Self-training with Noisy Student
3. ImageNet Classification With Deep Convolutional Neural Networks阅读笔记
4. ImageNet Classification with Deep Convolutional Neural Networks-AlexNet阅读笔记
5. ImageNet classification with deep convolutional neural networks阅读笔记
6. Reinforcement Learning for Relation Classification from Noisy Data阅读笔记
7. alexnet笔记（ImageNet Classification with Deep Convolutional Neural Networks）
8. Pre-training on Grayscale ImageNet Improves Medical Image Classification
9. ImageNet Classification with Deep Convolutional Neural Network读书笔记
10. ImageNet Classification with Deep Convolutional Neural Networks -- 解读

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