Image quality enhancement of a CD-SEM image using conditional generative adversarial networks
Y Midoh, K Nakamae - Metrology, Inspection, and Process …, 2019 - spiedigitallibrary.org
Critical dimension scanning electron microscopes (CD-SEMs) are widely used as the tool for
measuring the actual size, shape, and roughness of device patterns in the semiconductor …
measuring the actual size, shape, and roughness of device patterns in the semiconductor …
Wafer SEM image generation with conditional generative adversarial network
H Du, Z Shi - Journal of Physics: Conference Series, 2020 - iopscience.iop.org
Abstract Scanning Electron Microscope (SEM) images play an essential role in the analysis
and evaluation of the defects of the circuit in advanced integrated circuit manufacturing …
and evaluation of the defects of the circuit in advanced integrated circuit manufacturing …
Enforcing perceptual consistency on generative adversarial networks by using the normalised laplacian pyramid distance
In recent years there has been a growing interest in image generation through deep
learning. While an important part of the evaluation of the generated images usually involves …
learning. While an important part of the evaluation of the generated images usually involves …
Conditional image synthesis with auxiliary classifier gans
In this paper we introduce new methods for the improved training of generative adversarial
networks (GANs) for image synthesis. We construct a variant of GANs employing label …
networks (GANs) for image synthesis. We construct a variant of GANs employing label …
Learning by competing: Competitive multi-generator based adversarial learning
Generative adversarial networks (GANs) have been extensively used for dozens of image
enhancement and image translation applications, where several traditional and novel …
enhancement and image translation applications, where several traditional and novel …
Defect simulation in SEM images using generative adversarial networks
SEM image processing is an important part of semiconductor manufacturing. However, one
difficulty of SEM image processing is collecting enough defect-containing samples of defect …
difficulty of SEM image processing is collecting enough defect-containing samples of defect …
SEM image quality enhancement: an unsupervised deep learning approach
L Yu, W Zhou, L Pu, W Fang - Metrology, Inspection, and …, 2020 - spiedigitallibrary.org
Continuous reduction in pattern size, the primary path of advancement for the semiconductor
industry, has greatly increased resolution and throughput demands for defect inspection and …
industry, has greatly increased resolution and throughput demands for defect inspection and …
HRGAN: A generative adversarial network producing higher-resolution images than training sets
M Park, M Lee, S Yu - Sensors, 2022 - mdpi.com
The generative adversarial network (GAN) has demonstrated superb performance in
generating synthetic images in recent studies. However, in the conventional framework of …
generating synthetic images in recent studies. However, in the conventional framework of …
Learning-aware feature denoising discriminator
Although generative adversarial networks (GANs) show great prospects for the task of image
synthesis, the quality of synthesized images by existing GANs is sometimes inferior to real …
synthesis, the quality of synthesized images by existing GANs is sometimes inferior to real …
[HTML][HTML] The effect of loss function on conditional generative adversarial networks
Abstract Conditional Generative Adversarial Network (cGAN) is a general purpose approach
for many image-to-image translation tasks, which aims to translate images from one form to …
for many image-to-image translation tasks, which aims to translate images from one form to …