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公开(公告)号：US11908118B2
公开(公告)日：2024-02-20
申请号：US17387955
申请日：2021-07-28
Applicant: CITIC Dicastal Co., Ltd.
Inventor： Zuo Xu , Yuancheng Cao , Wuxin Sha , Zhihua Zhu , Hanqi Wu , Fanpeng Cheng
CPC classification number: G06T7/0002 , G06F18/214 , G06F18/217 , G06N3/08 , G06T7/20 , G06T7/62 , G06V10/30 , G06V20/695 , G06T2207/10056 , G06T2207/20081 , G06T2207/20084 , G06T2207/30241
Abstract: The present disclosure provides a visual model for image analysis of material characterization and analysis method thereof. By collecting and labeling big data of microscopic images, the present disclosure establishes an image data set of material characterization; and uses this data set for high-throughput deep learning, establishes a neural network model and dynamic statistical model based on deep learning, to identify and locate atomic or lattice defects, and automatically mark the lattice spacing, obtain the classification and statistics of the true shape of the microscopic particles of the material, quantitatively analyze the tissue dynamics of the material.
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公开(公告)号：US20220301139A1
公开(公告)日：2022-09-22
申请号：US17387955
申请日：2021-07-28
Applicant: CITIC Dicastal Co., Ltd.
Inventor： Zuo Xu , Yuancheng Cao , Wuxin Sha , Zhihua Zhu , Hanqi Wu , Fanpeng Cheng
Abstract: The present disclosure provides a visual model for image analysis of material characterization and analysis method thereof. By collecting and labeling big data of microscopic images, the present disclosure establishes an image data set of material characterization; and uses this data set for high-throughput deep learning, establishes a neural network model and dynamic statistical model based on deep learning, to identify and locate atomic or lattice defects, and automatically mark the lattice spacing, obtain the classification and statistics of the true shape of the microscopic particles of the material, quantitatively analyze the tissue dynamics of the material.
