Xqing_2016的博客

目录2021：PM2.5 Monitoring: Use Information Abundance Measurement and Wide and Deep Learning2020：FEATURE ENHANCEMENT AND FUSION FOR IMAGE-BASED PARTICLE MATTER ESTIMATION WITH F-MSE LOSS2021：PM2.5 Monitoring: Use Information Abundance Measurement and Wide an

目录1. Domain Adaptation for Image Dehazing (Yuanjie Shao, 2020)2. Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing (Deniz Engin, 2018)3. Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution (Yong Guo, 2020)4. PairedCycleG

目录摘要1. Introduction2. Related work2.1. Single Image Dehazing2.2. Domain Adaptation3. Proposed Method3.2. Image Translation Module The3.4. Training Losses论文信息：Domain Adaptation for Image Dehazing arXiv:2005.04668v1摘要目前大多数 learning-based 方法在合成雾图上训练去雾模型，很难

目录Haze Removal Using Dark Channel Prior4.2. Soft Matting前一篇博客介绍了论文的摘要、引言、背景以及暗通道先验部分，接下来继续介绍文章中余下的部分。Haze Removal Using Dark Channel Prior4.2. Soft Matting注意到公式（1）与图像抠图方程（image matting equation）有着相似的形式，所以我们采用了一个 soft matting 算法来改善透射（transmission）。sof

目录摘要1. Introduction2. Background3. Dark Channel Prior4. Haze Removal Using Dark Channel Prior4.1. Estimating the Transmission4.2. Soft Matting论文标题：Single Image Haze Removal Using Dark Channel Prior，一作：何凯明。摘要提出暗通道先验（dark channel prior）去除单一输入图像中的雾霾，该理论基于一