| 标题 |
  Deep learning in optical metrology: a review 光学计量中的深度学习：综述
相关领域
计量学
计算机科学
深度学习
人工智能
领域（数学）
人工神经网络
系统工程
机器学习
计算机工程
数据科学
工程类
物理
数学
光学
纯数学
|
| 网址 |
求助人暂未提供
|
| DOI |
暂未提供，该求助的时间将会延长，查看原因？
|
| 其它 |
C Zuo, J Qian, S Feng, W Yin, Y Li, P Fan, J Han, K Qian, Q Chen Light: Science & Applications, 2022•nature.com Abstract With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones in manufacturing, fundamental research, and engineering applications, such as quality control, nondestructive testing, experimental mechanics, and biomedicine. In recent years, deep learning, a subfield of machine learning, is emerging as a powerful tool to address problems by learning from data, largely driven by the availability of massive datasets, enhanced computational power, fast data storage, and novel training algorithms for the deep neural network. It is currently promoting increased interests and gaining extensive attention for its utilization in the field of optical metrology. |
| 求助人 | |
| 下载 | 该求助完结已超 24 小时，文件已从服务器自动删除，无法下载。 |
|
温馨提示：该文献已被科研通 学术中心 收录，前往查看
科研通『学术中心』是文献索引库，收集文献的基本信息（如标题、摘要、期刊、作者、被引量等），不提供下载功能。如需下载文献全文，请通过文献求助获取。
|
cdercder
wangrblzu
孙燕
从容芮
OCDer
zho
hjyylab
妖娃娃
个性归尘
可千万不要躺平呀
jyy
遇上就这样吧
morena
坚强的严青
zyp
YifanWang
nenoaowu
Oculus
elizabeth339
过氧化氢
皖公网安备34019202002308
