公开(公告)号：US09857314B1

公开(公告)日：2018-01-02

申请号：US15392713

申请日：2016-12-28

Applicant: Industrial Technology Research Institute

Inventor： Fu-Cheng Yang ,  Chia-Liang Yeh ,  Wei-Hsiung Tsai ,  Keng-Li Lin ,  Yeou-Sung Lin ,  Mao-Sheng Huang

IPC: G01J3/00 ,  G01N21/958 ,  G01N21/47 ,  G01N21/95

CPC classification number: G01N21/958 ,  G01N21/4788 ,  G01N2021/9513

Abstract: A device and method for detecting crystal quality of a low temperature poly-silicon (LTPS) backplane are provided, the method including: projecting narrowband light to the LTPS backplane; performing image capturing of each position on a surface of the LTPS backplane at a first angle in a first axial direction to obtain a first diffraction image, the first angle being an angle of maximum diffraction light intensity in the first axial direction; performing another image capturing of each position on the surface of the LTPS backplane at a second angle in a second axial direction to obtain a second diffraction image, the second angle being an angle of maximum diffraction light intensity in the second axial direction; and determining the crystal quality of the LTPS backplane based on a diffraction light intensity distribution obtained from the first and second diffraction images.

公开(公告)号：US12099053B2

公开(公告)日：2024-09-24

申请号：US17563701

申请日：2021-12-28

Applicant: INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE

Inventor： Hsiang-Chun Wei ,  Chih-Hsiang Liu ,  Chung-Lun Kuo ,  Chun-Wei Lo ,  Chia-Hung Cho ,  Wei-Hsiung Tsai

IPC: G01N33/50 ,  G01N15/1433 ,  G03H1/00 ,  G03H1/04 ,  G03H1/08 ,  G06T7/00

CPC classification number: G01N33/505 ,  G01N15/1433 ,  G03H1/0005 ,  G03H1/0443 ,  G03H1/0866 ,  G06T7/0012 ,  G03H2001/0033 ,  G03H2001/005 ,  G06T2207/10056 ,  G06T2207/10064 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024

Abstract: A method of training AI for label-free cell viability determination includes a step of providing a cell sample, a step of obtaining a fluorescence image and a DHM image of the cell sample, a step of determining a first cell viability of the cell sample according to the fluorescence image of the cell sample, a step of labeling the DHM image of the cell sample as a model specifying the first cell viability, and a step of performing AI training by using the model containing the DHM image of the cell sample.