
基本信息:
- 专利标题: 自动光学检测方法、设备、及其深度学习系统
- 专利标题(英):An automated optical inspection method using deep learning, and an optical inspection apparatus, computer program, computer readable medium, and deep learning system
- 申请号:CN201810189495.5 申请日:2018-03-08
- 公开(公告)号:CN109959661A 公开(公告)日:2019-07-02
- 发明人: 方志恒 , 陆家樑 , 徐敏堂 , 安比卡帕亚鲁木鲁甘 , 林建仲
- 申请人: 由田新技股份有限公司
- 申请人地址: 中国台湾新北市中和区连城路268号10楼之1
- 专利权人: 由田新技股份有限公司
- 当前专利权人: 由田新技股份有限公司
- 当前专利权人地址: 中国台湾新北市中和区连城路268号10楼之1
- 代理机构: 北京维澳专利代理有限公司
- 代理人: 王立民; 张应
- 优先权: 106145566 20171225 TW
- 主分类号: G01N21/88
- IPC分类号: G01N21/88
The present invention is an automated optical inspection method using deep learning, comprising the steps of: providing a plurality of paired image combinations, wherein each said paired image combination includes at least one defect-free image and at least one defect-containing image corresponding to the defect-free image; providing a convolutional neural network to start a training mode of the convolutional neural network; inputting the plurality of paired image combinations into the convolutional neural network, and adjusting a weight of at least one fully connected layer of the convolutional neural network through backpropagation to complete the training mode of the convolutional neural network; and performing an optical inspection process using the trained convolutional neural network.
IPC结构图谱:
G | 物理 |
--G01 | 测量;测试 |
----G01N | 借助于测定材料的化学或物理性质来测试或分析材料 |
------G01N21/00 | 利用光学手段,即利用红外光、可见光或紫外光来测试或分析材料 |
--------G01N21/01 | .便于进行光学测试的装置或仪器 |
----------G01N21/88 | ..测试瑕疵、缺陷或污点的存在 |