Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434. 2015. Henderson M, Shakya S, Pradhan S, Cook T. Quanvolutional neural networks: powering image recognition with quantum circuits. Quantum Machine Intelligence. 2020;2:1–9. ...
Adversarial lossMost of the papers related to conditional GANs, use vanilla GAN objective as the loss[20][25] function. Recently [47] provides an alternative way of using least aquare GAN [23] which is more stable and generates higher quality results. We use WGAN-GP [11] as the critic ...
Residual networkDeep convolutional neural networkRecently, generative adversarial network (GAN) has been widely employed in single image super-resolution (SISR), achieving favorably good perceptual effects. However, the SR outputs generated by GAN still have some fictitious details, which are quite ...
Adversarial lossMost of the papers related to conditional GANs, use vanilla GAN objective as the loss[20][25] function. Recently [47] provides an alternative way of using least aquare GAN [23] which is more stable and generates higher quality results. We use WGAN-GP [11] as the critic ...
3.3 Conditional Domain Adversarial Network 我们使条件对抗的领域适应f在特定领域的特征表示和分类器预测g。我们共同减少(1)w.r.t.来源分类器g和f特征提取器,减少(2)w.r.t.域鉴别器D, f和最大化(2)w.r.t.特征提取器和源分类器g .这个收益率条件的极大极小问题域对抗网络(CDAN) ...
Image-to-Image Translation with Conditional Adversarial Networks Phillip Isola Jun-Yan Zhu Tinghui Zhou Alexei A. Efros Berkeley AI Research (BAIR) Laboratory, UC Berkeley Labels to Street Scene Labels to Facade BW to Color input Aerial to Map output input output Day to Night input output Edg...
而在CVPR2017上,一篇由Isola等人提出的《Image-to-Image Translation with Conditional Adversarial Networks》的论文更是使用条件生成式对抗网络(cGAN)开启了“image-to-image translation”任务的大门。 Example results on several image-to-image translation problems. 本文的思想主要受近期图像超分辨率重建和“image-...
{N}}\). The first two entries correspond to the auxiliary tokens, which are treated like ordinary atoms by the neural network. Thus, whenever we refer to atoms in the following, this also encompasses the tokens. Note that tokens do not influence the sampling probability of a molecule in ...
Conditional Adversarial Domain Adaptation Neural Network for Motor Imagery EEG Decoding. Entropy. 2020; 22(1):96. https://doi.org/10.3390/e22010096 Chicago/Turabian Style Tang, Xingliang, and Xianrui Zhang. 2020. "Conditional Adversarial Domain Adaptation Neural Network for Motor Imagery EEG ...
generative adversarial network; convolutional neural network; consistent image-to-image translation network; autoencoders1. Introduction Translating images between different domains has many important applications in the field of robotics and computer vision, including terrain shape estimation, tip-over and ...