公开(公告)号：US20210201460A1

公开(公告)日：2021-07-01

申请号：US16925243

申请日：2020-07-09

Applicant: MICRON TECHNOLOGY, INC.

Inventor： Yutao Gong ,  Dmitry Vengertsev ,  Seth A. Eichmeyer ,  Jing Gong

IPC: G06T7/00 ,  G01N21/95

Abstract: An inspection system for determining wafer defects in semiconductor fabrication may include an image capturing device to capture a wafer image and a classification convolutional neural network (CNN) to determine a classification from a plurality of classes for the captured image. Each of the plurality of classes indicates a type of a defect in the wafer. The system may also include an encoder to encode to convert a training image into a feature vector; a cluster system to cluster the feature vector to generate soft labels for the training image; and a decoder to decode the feature vector into a re-generated image. The system may also include a classification system to determine a classification from the plurality of classes for the training image. The encoder and decoder may he formed from a CNN autoencoder. The classification CNN and the CNN autoencoder may each be a deep neural network.

公开(公告)号：US20240273388A1

公开(公告)日：2024-08-15

申请号：US18642101

申请日：2024-04-22

Applicant: MICRON TECHNOLOGY, INC.

Inventor： Yi Hu ,  Dmitry Vengertsev ,  Zahra Hosseinimakarem ,  Jonathan D. Harms

IPC: G06N5/04 ,  G06N20/00 ,  G06T7/00 ,  G06T7/521 ,  G06T7/90 ,  G06T11/00

CPC classification number: G06N5/04 ,  G06N20/00 ,  G06T7/521 ,  G06T7/90 ,  G06T7/97 ,  G06T11/001

Abstract: An image or a spectrum of a surface may be acquired by a computing device, which may be included in a mobile device in some examples. The computing device may extract a measured spectrum from the image and generate a corrected spectrum of the surface. In some examples, the corrected spectrum may be generated to compensate for ambient light influence. The corrected spectrum may be analyzed to provide a result, such as a diagnosis or a product recommendation. In some examples, the result is based, at least in part, on a comparison of the corrected spectrum to reference spectra. In some examples, the result is based, at least in part, on an inference of a machine learning model.

公开(公告)号：US11995567B2

公开(公告)日：2024-05-28

申请号：US17005036

申请日：2020-08-27

Applicant: MICRON TECHNOLOGY, INC.

Inventor： Yi Hu ,  Dmitry Vengertsev ,  Zahra Hosseinimakarem ,  Jonathan D. Harms

IPC: G06N5/04 ,  G06N20/00 ,  G06T7/00 ,  G06T7/521 ,  G06T7/90 ,  G06T11/00

CPC classification number: G06N5/04 ,  G06N20/00 ,  G06T7/521 ,  G06T7/90 ,  G06T7/97 ,  G06T11/001

Abstract: An image or a spectrum of a surface may be acquired by a computing device, which may be included in a mobile device in some examples. The computing device may extract a measured spectrum from the image and generate a corrected spectrum of the surface. In some examples, the corrected spectrum may be generated to compensate for ambient light influence. The corrected spectrum may be analyzed to provide a result, such as a diagnosis or a product recommendation. In some examples, the result is based, at least in part, on a comparison of the corrected spectrum to reference spectra. In some examples, the result is based, at least in part, on an inference of a machine learning model.

公开(公告)号：US11861493B2

公开(公告)日：2024-01-02

申请号：US16854107

申请日：2020-04-21

Applicant: MICRON TECHNOLOGY, INC.

Inventor： Dmitry Vengertsev ,  Zahra Hosseinimakarem ,  Jonathan D. Harms

IPC: G06N3/08 ,  G06N3/04 ,  G06F18/24 ,  G06F18/214 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06N3/08 ,  G06F18/214 ,  G06F18/24 ,  G06N3/04 ,  G06V10/764 ,  G06V10/82

Abstract: Data may be abstracted and/or masked prior to being provided to a machine learning model for training. A machine learning model may provide a confidence level associated with a result. If the confidence level is too high, the machine learning model or an application including the machine learning model may refrain from providing the result as an output. In some examples, the machine learning model may provide a “second best” result that has an acceptable confidence level. In other examples, an error signal may be provided as the output. In accordance with examples of the present disclosure, data may be abstracted and/or masked prior to being provided to a machine learning model for training and confidence levels of results of the trained machine learning model may be used to determine when a result should be withheld.

公开(公告)号：US20220067491A1

公开(公告)日：2022-03-03

申请号：US17006602

申请日：2020-08-28

Applicant: Micron Technology, Inc.

Inventor： Dmitry Vengertsev ,  Stewart R. Watson ,  Jing Gong ,  Ameya Parab

IPC: G06N3/063 ,  G06N3/08 ,  G06N7/00 ,  G06N5/04 ,  G11C13/00 ,  H03M1/36

Abstract: Apparatuses and methods can be related to implementing a Bayesian neural network in a memory. A Bayesian neural network can be implemented utilizing a resistive memory array. The memory array can comprise programmable memory cells that can be programed and used to store weights of the Bayesian neural network and perform operations consistent with the Bayesian neural network.

公开(公告)号：US20210372785A1

公开(公告)日：2021-12-02

申请号：US16890364

申请日：2020-06-02

Applicant: MICRON TECHNOLOGY, INC.

Inventor： Zahra Hosseinimakarem ,  Jonathan D. Harms ,  Alyssa N. Scarbrough ,  Dmitry Vengertsev ,  Yi Hu

IPC: G01B11/30

Abstract: Embodiments of the disclosure are drawn to projecting light on a surface and analyzing the scattered light to obtain spatial information of the surface and generate a three dimensional model of the surface. The three dimensional model may then be analyzed to calculate one or more surface characteristics, such as roughness. The surface characteristics may then be analyzed to provide a result, such as a diagnosis or a product recommendation. In some examples, a mobile device is used to analyze the surface.