桑梅
- 教师拼音名称：SANG MEI
- 出生日期：1967-05-02
- 职务：Vice head of department of Optoelectronics
- 性别：女
- 职称：教授
- 所属院系：精密仪器与光电子工程学院
Unsupervised anomaly detection of MEMS in low illumination based on polarimetric Support Vector Data Description
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- 所属单位:天津大学
- 发表刊物:光学快报
- 刊物所在地:美国
- 项目来源:国家重点研发计划项目
- 关键字:无监督缺陷检测，偏振增强，
- 摘要:Lowilluminated images make it challenging to conduct anomaly detection on materialsurface. Adding polarimetric information helps expand pixel range and recover background structure of network inputs. In this letter, an anomaly detection method in low illumination is proposed which utilizes polarization imaging and patch-wise Support Vector Data Description (SVDD) model. Polarimetric information of Micro Electromechanical System (MEMS) surface is captured by a division-of-focal- plane (DoFP) polarization camera and used to enhance low illuminated images. The enhanced images without defects ser
- 合写作者:黄耀慷，桑梅，邢伦，胡浩丰，刘铁根
- 第一作者:黄耀慷
- 论文类型:Applied Research
- 通讯作者:桑梅
- 卷号:29
- 期号:22
- 页面范围:35651-35663
- 是否译文:否
- CN号:null