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G Hu 著2020被引用数: 26 — Radford, A, Luke, M, Chintala, S. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint ...
G Hu 著2020被引用数: 26 — The generative adversarial network (GAN) was originally proposed by Goodfellow et al., and it is a framework for learning generative models of ...

In this paper we present a novel unsupervised method for automatically detecting defects in fabrics based on a deep convolutional generative adversarial network ...
G Hu 著2020被引用数: 26 — ... present a novel unsupervised method for automatically detecting defects in fabrics based on a deep convolutional generative adversarial network (DCGAN).
J Wang 著2021 — Keywords: defect detection; texture analysis; deep convolution generative adversarial network. (DCGAN); unsupervised learning. 1.
论文阅读笔记《Unsupervised fabric defect detection based on a deep convolutional GAN》. 深视 2020-11-02 16:32:51 786 收藏 7. 分类专栏: 论文阅读笔记 # 缺陷 ...
[13] suggested a new unsupervised approach for detecting fabric defects on the basis of the. Deep Convolutional Generative Adversarial Network (DCGAN) and ...
Xin Geng、 Byeong-Ho Kang — 2018Computers
Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for ... Langs, G.: Unsupervised anomaly detection with generative adversarial networks to ...
A Rasheed 著被引用数: 2 — [77] proposed unsupervised learning approach based on deep convolutional generative adversarial network (DCGAN) to locate the surface defects for texture.
... An unsupervised learning approach based on deep convolutional generative adversarial network (DCGAN) to locate the surface defects for texture.

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