LARGE SCALE IMAGE COMPLETION VIA CO-MODULATED 清华和微软的工作。 解读一下题目: large scale 大尺度 image completion 图像补全 co-modulated 互协调 generative adversarial network 生成对抗网络 梳理一下:课题中提出一种 互协调 生成对抗网络,用来解决大尺度图像的补全问题。 核心思想 如何在大尺信息缺失的情况下...
3.1. Generative adversarial networks (GANs) GANs have recently been employed for numerous healthcare-related applications, particularly SARS-CoV-2 [[149], [150], [151]]. A GAN is an approach based on a deep learning technique that consists of two models: a generator and a discriminator [152...
The AI model may include a plurality of neural network layers. Each layer has a plurality of weight values and performs a layer operation through the calculation of a previous layer and an operation of a plurality of weights. Examples of neural networks include, but are not limited to, convol...
as shown in Fig.3, which improves the generator part based on the original conditional StyleGAN2. Combining the good generation performance of the unconditional StyleGAN2 generative model and the training method of StyleGAN2 that focuses on the whole first and then supplements...
proposed a photonic Generative adversarial network (GAN) and the corresponding noise-aware training approaches [104]. After training with noise-aware training methodologies, namely, the input-compensatory approach (IC-GAN) and the kernel weight-compensatory approach (WC-GAN), the photonic generative ...