文献阅读笔记6 Convolutional Neural Networks for No-Reference Image Quality Assessment（KANG）

时间 2021-01-02

标签 IQA 繁體版

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Convolutional Neural Networks for No-Reference Image Quality Assessment 摘要该网络由一个具有最大和最小池的卷积层、两个完全连接的层和一个输出节点组成，在网络结构中，特征学习和回归。 3 CNN for NR-IQA 提出了利用CNN对图像质量进行估计的框架如下：给定灰度图像，先进行对比度归一化，然后对不重叠的子块进行采样，然

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1. Two-Stream Convolutional Networks for Blind Image Quality Assessment
2. Convolutional Neural Networks for No-Reference Image Quality Assessment 论文翻译
3. 图像质量评估 (IQA) 论文笔记： Convolutional Neural Networks for No-Reference Image Quality Assessment
4. Face-Image-Quality-Assessment
5. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks-文献阅读笔记
6. 《Bag of Tricks for Image Classification with Convolutional Neural Networks》论文阅读笔记
7. Stereoscopic image quality assessment by deep convolutional neural network
8. Convolutional Neural Networks for Sentence Classification 阅读笔记
9. RankIQA:Learning from Rankings for No-reference Image Quality Assessment论文阅读笔记
10. 文献阅读笔记5 On the Use of Deep Learning for Blind Image Quality Assessment（2D）

>>更多相关文章<<