公开(公告)号：US20230032587A1

公开(公告)日：2023-02-02

申请号：US17855888

申请日：2022-07-01

Applicant: Hitachi High-Tech Corporation

Inventor： Takahiro NISHIHATA ,  Yuji TAKAGI ,  Takuma YAMAMOTO ,  Yasunori GOTO ,  Yasutaka TOYODA

IPC: H01J37/22 ,  H01J37/28 ,  G01N23/2251

Abstract: A method, an apparatus, and a program for more appropriately determining a condition for appropriately recognizing a semiconductor pattern are provided. A method for determining a condition related to a captured image of a charged particle beam apparatus including: acquiring, by a processor, a plurality of captured images, each of the captured images being an image generated by irradiating a pattern formed on a wafer with a charged particle beam, and detecting electrons emitted from the pattern, each of the captured images being an image captured according to one or more imaging conditions, the method further including: acquiring teaching information for each of the captured images; acquiring, by the processor, one or more feature determination conditions; calculating, by the processor, a feature for each of the captured images based on each of the feature determination conditions, at least one of the imaging condition and the feature determination condition being plural.

公开(公告)号：US20220318975A1

公开(公告)日：2022-10-06

申请号：US17596025

申请日：2019-06-13

Applicant: Hitachi High-Tech Corporation

Inventor： Masanori OUCHI ,  Shinichi SHINODA ,  Yasutaka TOYODA ,  Ryou YUMIBA ,  Hiroyuni SHINDO

IPC: G06T7/00 ,  G06T9/00

Abstract: The purpose of the present invention is to provide a computer program for achieving die-to-database inspection at high speed and with few false reports, and a semiconductor inspection device using the same. To achieve this purpose, the present invention proposes: a computer program comprising an encoder layer that is configured to determine the features of a design data image, and a decoder layer that is configured to generate, on the basis of a variation in an image (inspection target image) obtained by photographing an inspection target pattern, a statistic pertaining to the brightness values of pixels from feature values output by the encoder layer, wherein die-to-database inspection with few false reports can be achieved by comparing the inspection target image and the statistic obtained from the decoder layer and pertaining to the brightness values, and thereby detecting a defect region in the image; and a semiconductor inspection device using the same.

公开(公告)号：US20240144560A1

公开(公告)日：2024-05-02

申请号：US18279921

申请日：2022-03-03

Applicant: Hitachi High-Tech Corporation

Inventor： Zhaohui CHENG ,  Yasutaka TOYODA ,  Hideto DOHI ,  Hiroya OHTA ,  Hideyuki KAZUMI

IPC: G06T11/60 ,  G06T5/80 ,  G06T7/13

CPC classification number: G06T11/60 ,  G06T5/80 ,  G06T7/13 ,  G06T2207/20081

Abstract: A training method that performs learning using appropriate low-quality image and high-quality image is provided. The invention is directed to a training method including executing learning by inputting a first image generated under a first image generation condition and a second image generated under a second image generation condition different from the first image generation condition to a learning apparatus that adjusts parameters so as to suppress an error between an input image and a converted image, in which the second image is selected such that an index value extracted from the second image is the same as or has a predetermined relationship with an index value extracted from the first image, or the second image is output from a second image generation tool different from a first image generation tool for generating the first image.

公开(公告)号：US20230222764A1

公开(公告)日：2023-07-13

申请号：US18009890

申请日：2020-06-16

Applicant: Hitachi High-Tech Corporation

Inventor： Masanori OUCHI ,  Masayoshi ISHIKAWA ,  Yasutaka TOYODA ,  Hiroyuki SHINDO

IPC: G06V10/75 ,  G06T7/00 ,  G06V10/74

CPC classification number: G06V10/751 ,  G06T7/0006 ,  G06V10/758 ,  G06V10/761 ,  G06T2207/30148

Abstract: An image processing method whereby data pertaining to an estimated captured image obtained from reference data of a sample is acquired using an input acceptance unit, an estimation unit, and an output unit. The data is used when comparing the estimated image and an actual image of the sample, wherein the method includes: an input acceptance unit accepting input of the reference data, process information pertaining to the sample, and trained model data; the estimation unit using the reference data, the process information, and the model data to calculate captured image statistics representing a probabilistic distribution of values attained by the data of the captured image; and the output unit outputting the captured image statistics, and generating the estimated captured image from the captured image statistics. This permits reducing the time required for estimation and to perform comparison in real time.

公开(公告)号：US20220415024A1

公开(公告)日：2022-12-29

申请号：US17781295

申请日：2020-01-09

Applicant: Hitachi High-Tech Corporation

Inventor： Yasutaka TOYODA ,  Masayoshi ISHIKAWA ,  Masanori OUCHI

IPC: G06V10/776 ,  G06T7/11 ,  G06V10/774 ,  G06V10/98 ,  G06T5/50

Abstract: This disclosure relates to a system for performing efficient learning of a specific portion. To achieve this purpose, there is proposed a system configured to generate a converted image on the basis of input of an input image, the system comprising a learning model in which parameters are adjusted so as to suppress an error between the input image and a second image converted upon input of the input image, the learning model being subjected to different learning at least between a first area in the image and a second area different from the first area.

公开(公告)号：US20220130027A1

公开(公告)日：2022-04-28

申请号：US17296421

申请日：2019-02-15

Applicant: Hitachi High-Tech Corporation

Inventor： Muneyuki FUKUDA ,  Yasutaka TOYODA ,  Ryou YUMIBA ,  Shuyang DOU ,  Ayumi DOI ,  Junichi TANAKA

IPC: G06T7/00 ,  H01L21/66 ,  G06V10/82 ,  G06V20/69 ,  G06T7/70 ,  G06T7/62 ,  G01N23/18 ,  G01N23/225

Abstract: The present disclosure relates to a system and a non-transitory computer-readable medium for estimating the height of foreign matter, etc. adhering to a sample. In order to achieve the abovementioned purpose, proposed is a system, etc. in which data acquired by a charged particle beam device or features extracted from the data are input to a learning model, which is provided with, in an intermediate layer thereof, a parameter learned using teacher data having data acquired by the charged particle beam device or features extracted from the data as inputs and having the heights or depths of the structures of samples or of foreign matter on the samples as outputs, and height or depth information is output.

公开(公告)号：US20220036116A1

公开(公告)日：2022-02-03

申请号：US17503438

申请日：2021-10-18

Applicant: Hitachi High-Tech Corporation

Inventor： Shinichi SHINODA ,  Yasutaka TOYODA ,  Shigetoshi SAKIMURA ,  Masayoshi ISHIKAWA ,  Hiroyuki SHINDO ,  Hitoshi SUGAHARA

IPC: G06K9/46 ,  G06K9/62 ,  G06T7/00

Abstract: An object of the present invention is to achieve both suppression of data amount of an image processing system that learns a collation image to be used for image identification using a discriminator and improvement of identification performance of the discriminator. In order to achieve the above object, there is proposed an image processing system including a discriminator that identifies an image using a collation image, the image processing system further including a machine learning engine that performs machine learning of collation image data required for image identification. The machine learning engine searches for a successfully identified image using an image for which identification has been failed, and adds information, obtained based on a partial image of the image for which identification has been failed and which has been selected by an input device to the successfully identified image obtained by the search to generate corrected collation image data.

公开(公告)号：US20250054270A1

公开(公告)日：2025-02-13

申请号：US18718670

申请日：2021-12-17

Applicant: Hitachi High-Tech Corporation

Inventor： Toshinori YAMAUCHI ,  Yasuhiro YOSHIDA ,  Masayoshi ISHIKAWA ,  Takefumi KAKINUMA ,  Masaki HASEGAWA ,  Kentaro OHIRA ,  Yasutaka TOYODA

IPC: G06V10/44 ,  G06T7/00 ,  G06T7/70 ,  G06V10/762 ,  G06V10/774 ,  G06V20/70

Abstract: Provided is a training data creation assistance device which, for an image on which a plurality of defects in an image are reflected, enables the efficient collection/selection of a training image by specifying a feature amount corresponding to each of the defects in a way that a peripheral area of the defect is also considered and by mapping the specified feature amount to a low dimensional space. The training data creation assistance device is characterized by comprising: an image recognition unit which, on the basis of a trained result, extracts feature amounts from an input image, performs image processing with the feature amounts, and outputs a recognition result; a feature amount specification unit which receives an input of one or more prediction results or designated areas from the image recognition unit, and specifies the feature amounts respectively corresponding to the prediction results or designated areas; an inspection result feature amount database in which the feature amounts of the respective prediction results or designation areas are stored; and a dimension reduction unit which performs dimensional reduction on the feature amounts stored in the inspection result feature amount database, and projects the feature amounts into a low-dimensional space, wherein the feature amount specification unit includes an important region calculation unit which, for each of the prediction results or each of the designated areas, obtains an important area that holds peripheral area information including a detected area of the prediction result or the designated area; and a feature amount extraction unit which extracts the feature value corresponding to each of the prediction results or each of the designated areas by weighting the feature value extracted by the image recognition unit in the importance area.

公开(公告)号：US20230298137A1

公开(公告)日：2023-09-21

申请号：US18021219

申请日：2020-09-29

Applicant: Hitachi High-Tech Corporation

Inventor： Masayoshi ISHIKAWA ,  Sota KOMATSU ,  Yasutaka TOYODA ,  Shinichi SHINODA

IPC: G06T5/00 ,  G06T5/50 ,  G06T7/00

CPC classification number: G06T5/001 ,  G06T5/50 ,  G06T7/0004 ,  G06T2207/20081 ,  G06T2207/30168 ,  G06T2207/20084 ,  G06T2207/30148 ,  G06T2207/10056

Abstract: An image quality improvement system includes: an image quality improvement unit that improves the image quality of a low quality image; a deformation prediction unit that predicts a deformation amount that has occurred between a first low quality image and a different second low quality image, included in a series of input low quality images; and a deformation correction unit that corrects, based on the deformation amount predicted by the deformation prediction unit, one of a first prediction image obtained by applying processing by the image quality improvement unit to the first low quality image, the second low quality image, or a second prediction image obtained by applying processing by the image quality improvement unit to the second low quality image. The image quality improvement system learns to reduce the evaluation of a loss function between the first prediction and the second low quality image or the second prediction image.

公开(公告)号：US20220067902A1

公开(公告)日：2022-03-03

申请号：US17418345

申请日：2019-10-11

Applicant: Hitachi High-Tech Corporation

Inventor： Shuyang DOU ,  Yasutaka TOYODA ,  Fumihiro BEKKU ,  Takefumi KAKINUMA ,  Shinichi SHINODA

IPC: G06T7/00 ,  G06K9/62 ,  G06K9/32 ,  G06N20/00

Abstract: The purpose of the present invention is to provide an image evaluation device and method which can detect unknown defects and which can prevent misrecognition by a machine learning model. This image evaluation device, which uses a machine learning classifier to classify defect information in a defect image of an electronic device, is characterized by being provided with: an image storage unit which stores a defect image of an electronic device; a defect region storage unit which stores defect region information that is in the defect image; a classifier which classifies the defect information with machine learning; an image extraction unit which, in the course of the defect image classification processing, extracts image-of-interest information which the classifier will focus on; and an evaluation unit which compares the image-of-interest information and the defect region information to evaluate the classifiability of the defect image.