Yi Liu1, Fumin Wang1, Zhili Jiang1

  • 1Institute of Process Equipment and Control Engineering, Zhejiang University of Technology, Hangzhou 310023, China.

PubMed
概括

这项研究利用深度学习增强了红外热学技术,用于对艺术品进行检查. 光谱规范生成对抗网络 (SNGAN) 和卷积自编码器 (CAE) 通过增加信号噪声比提高了缺陷检测.

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