cvpr2020中的论文:Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution 论文连接arxiv.org/pdf/2003.07018.pdf 代码连接github.com/guoyongcs/DRN 论文摘要: 抛出了SISR中的两个限制: 1.学习从LR到HR图像的映射函数是一个典型的不适定问题,因为存在无限个HR图像可以下采样到相...
《Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution》 从LR映射到HR是一个不适定问题,而且在现实中不容易获取大量的LR-HR成对的训练数据,且LR的退化方法是未知的。现有的超分辨方法还存在过拟合问题,导致在实际应用中性能低下。基于这些问题,该文章作者提出了双支路的回归网络,将LR...
Security Insights Additional navigation options master BranchesTags Code README MIT license Pytorch implementation for "Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution". Important Update We released the code and models of ourDual Regression Compression (DRC)towards lightweigh...
Therefore, this paper proposes a blind image super-resolution reconstruction algorithm based on dual regression, which aims to solve the problem of poor performance of super-resolution networks in real scenes. Firstly, the closed-loop network is used to constrain the mapping space, and the optimal...
For example, if you have two groups of subjects (patients and controls), did a group-ICA on the basis of all subjects from both groups, and then run dual-regression. You then did a two-group t-test using the spatial maps output by dual-regression, and found a significant difference for...
In this paper, we propose a method to transform features of different signals into different regression values, and use these values to distinguish different signals. The contributions of proposed method are described as follow: Firstly, we design a dual-input neural network to fuse and map the ...
In Proc. International Conference on Neural Networks 1930–1935 (IEEE, 1997). Bates, D., Machler, M., Bolker, B. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2014). Google Scholar Tibshirani, R. Regression shrinkage and selection ...
Dual Path Networks share common features while maintaining the flexibility to explore new features through dual path architectures. We formulate such a dual path architecture as follows:$$x^{k} = \sum\limits_{t=1}^{k-1} f_t^{k}(h^t) \text{,} $$$y^{k} = \sum\limits_{t=1}^...
Su X, Li J, Hua Z (2022) Transformer-based regression network for pansharpening remote sensing images. IEEE Trans Geosci Remote Sens 60:1–23 Google Scholar Su Y, Zhu H, Wong KC, Chang Y, Li X (2022) Hyperspectral image denoising via weighted multidirectional low-rank tensor recovery. ...
To test our hypotheses, we run logistic regression models predicting good health, stratified by gender, with adjusted standard errors to account for the non-independence of cases within the same country. Moreover, to correct for different probabilities of being sampled across countries, the data are...