公开(公告)号：US20230316493A1

公开(公告)日：2023-10-05

申请号：US18320866

申请日：2023-05-19

Applicant: Samsung Display Co., Ltd.

Inventor： Yan Kang ,  Janghwan Lee ,  Shuhui Qu ,  Jinghua Yao ,  Sai MarapaReddy

IPC: G06T7/00 ,  G06N3/08 ,  G06N20/20 ,  G06V10/82 ,  G06V10/70 ,  G06F18/241 ,  G06F18/25 ,  G06N3/045 ,  G06V20/69

CPC classification number: G06T7/0004 ,  G06N3/08 ,  G06N20/20 ,  G06V10/82 ,  G06V10/70 ,  G06F18/241 ,  G06F18/251 ,  G06N3/045 ,  G06V20/69 ,  G06T2207/10056 ,  G06T2207/20084 ,  G06T2207/20081 ,  G06T2207/10116

Abstract: A system for manufacturing defect classification is presented. The system includes a first neural network receiving a first data as input and generating a first output, a second neural network receiving a second data as input and generating a second output, wherein first neural network and the second neural network are trained independently from each other, and a fusion neural network receiving the first output and the second output and generating a classification. The first data and the second data do not have to be aligned. Hence, the system and method of this disclosure allows various type of data that are collected during manufacturing to be used in defect classification.

公开(公告)号：US20210096530A1

公开(公告)日：2021-04-01

申请号：US16693101

申请日：2019-11-22

Applicant: Samsung Display Co., Ltd.

Inventor： Sai MarapaReddy ,  Shuhui Qu ,  Janghwan Lee

IPC: G05B19/406 ,  G06N3/08

Abstract: A system and method for classifying products manufactured via a manufacturing process. A processor receives an input dataset, and extracts features of the input dataset at two or more levels of abstraction. The processor combines the extracted features and provides the combined extracted features to a classifier. The classifier is trained based on the combined extracted features for learning a pattern of not-faulty products. The trained classifier is configured to receive data for a product to be classified, to output a prediction for the product based on the received data.

公开(公告)号：US12136205B2

公开(公告)日：2024-11-05

申请号：US18320866

申请日：2023-05-19

Applicant: Samsung Display Co., Ltd.

Inventor： Yan Kang ,  Janghwan Lee ,  Shuhui Qu ,  Jinghua Yao ,  Sai MarapaReddy

IPC: G06T7/00 ,  G06F18/241 ,  G06F18/25 ,  G06N3/045 ,  G06N3/08 ,  G06N20/20 ,  G06V10/70 ,  G06V10/82 ,  G06V20/69

Abstract: A system for manufacturing defect classification is presented. The system includes a first neural network receiving a first data as input and generating a first output, a second neural network receiving a second data as input and generating a second output, wherein first neural network and the second neural network are trained independently from each other, and a fusion neural network receiving the first output and the second output and generating a classification. The first data and the second data do not have to be aligned. Hence, the system and method of this disclosure allows various type of data that are collected during manufacturing to be used in defect classification.

公开(公告)号：US20220343140A1

公开(公告)日：2022-10-27

申请号：US17317806

申请日：2021-05-11

Applicant: Samsung Display Co., Ltd.

Inventor： Shuhui Qu ,  Janghwan Lee ,  Yan Kang

IPC: G06N3/04 ,  G06N3/08

Abstract: Systems and method for classifying manufacturing defects are disclosed. A first machine learning model is trained with a training dataset, and a data sample that satisfies a criterion is identified from the training dataset. A second machine learning model is trained to learn features of the data sample. When an input dataset that includes first and second product data is received, the second machine learning model is invoked for predicting confidence of the first and second product data based on the learned features of the data sample. In response to predicting the confidence of the first and second product data, the first product data is removed from the dataset, and the first machine learning model is invoked for generating a classification based the second product data.

公开(公告)号：US12301833B2

公开(公告)日：2025-05-13

申请号：US18074195

申请日：2022-12-02

Applicant: Samsung Display Co., Ltd.

Inventor： Shuhui Qu ,  Qisen Cheng ,  Yannick Bliesener ,  Janghwan Lee

IPC: H04N19/157 ,  G06V10/44 ,  G06V10/74 ,  G06V20/40 ,  H04N19/94

Abstract: According to some embodiments, a system includes: a memory, an encoder; a decoder, wherein the system is operable to: receive, at the encoder, an input video; divide, by the encoder, the input video into a plurality of video patches; select, by the encoder, codes corresponding to the plurality of video patches of the input video, from a codebook comprising the codes; determine, by the encoder, an assigned code matrix comprising the codes corresponding to the plurality of video patches of the input video; receive, by the decoder, the assigned code matrix from the encoder; and generate, by the decoder, a reconstructed video based on the assigned code matrix.

公开(公告)号：US20240127030A1

公开(公告)日：2024-04-18

申请号：US18109710

申请日：2023-02-14

Applicant: Samsung Display Co., Ltd.

Inventor： Qisen Cheng ,  Shuhui Qu ,  Kaushik Balakrishnan ,  Janghwan Lee

IPC: G06N3/042 ,  G06N5/01

CPC classification number: G06N3/042 ,  G06N5/01

Abstract: A classification system includes: one or more processors; and memory including instructions that, when executed by the one or more processors, cause the one or more processors to: calculate reference Shapley values for features of a data sample based on a first classification model; and train a second classification model though multi-task distillation to: predict Shapley values for the features of the data sample based on the reference Shapley values and a distillation loss; and predict a class label for the data sample based on the predicted Shapley values and a ground truth class label for the data sample.

公开(公告)号：US11694319B2

公开(公告)日：2023-07-04

申请号：US16938812

申请日：2020-07-24

Applicant: Samsung Display Co., Ltd.

Inventor： Yan Kang ,  Janghwan Lee ,  Shuhui Qu ,  Jinghua Yao ,  Sai MarapaReddy

IPC: G06T7/00 ,  G06N3/08 ,  G06N20/20 ,  G06V10/82 ,  G06V10/70 ,  G06F18/241 ,  G06F18/25 ,  G06N3/045 ,  G06V20/69

CPC classification number: G06T7/0004 ,  G06F18/241 ,  G06F18/251 ,  G06N3/045 ,  G06N3/08 ,  G06N20/20 ,  G06V10/70 ,  G06V10/82 ,  G06V20/69 ,  G06T2207/10056 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: A system for manufacturing defect classification is presented. The system includes a first neural network receiving a first data as input and generating a first output, a second neural network receiving a second data as input and generating a second output, wherein first neural network and the second neural network are trained independently from each other, and a fusion neural network receiving the first output and the second output and generating a classification. The first data and the second data do not have to be aligned. Hence, the system and method of this disclosure allows various type of data that are collected during manufacturing to be used in defect classification.

公开(公告)号：US20220374720A1

公开(公告)日：2022-11-24

申请号：US17367179

申请日：2021-07-02

Applicant: Samsung Display Co., Ltd.

Inventor： Shuhui Qu ,  Janghwan Lee ,  Yan Kang

IPC: G06N3/08 ,  G06K9/62 ,  G06K9/74 ,  G06N3/063

Abstract: Systems and methods for classifying products are disclosed. A first data sample having a first portion and a second portion is identified from a training dataset. A first mask is generated based on the first data sample, where the first mask is associated with the first portion of the first data sample. A second data sample is generated based on a noise input. The first mask is applied to the second data sample for outputting a third portion of the second data sample. The third portion of the second data sample is combined with the second portion of the first data sample for generating a first combined data sample. Confidence and classification of the first combined data sample are predicted. The first combined data sample is added to the training dataset in response to predicting the confidence and the classification.

公开(公告)号：US20240312193A1

公开(公告)日：2024-09-19

申请号：US18339075

申请日：2023-06-21

Applicant: Samsung Display Co., Ltd.

Inventor： Qisen Cheng ,  Shuhui Qu ,  Kaushik Balakrishnan ,  Janghwan Lee

IPC: G06V10/80 ,  G06N3/0455 ,  G06T7/00

CPC classification number: G06V10/803 ,  G06N3/0455 ,  G06T7/0004 ,  G06T2207/20081

Abstract: A method may include providing a data set including rows of data. The rows of data may include at least one row of unpaired modality including a first modality, and at least one row of paired modality may include both the first modality and a second modality. The method may further include imputing, by a modality-specific encoder, the at least one row of unpaired modality by interpolating embeddings from the second modality of the paired modality; training, in a latent space, the modality-specific encoder based on the imputation for unimodal prediction and bimodal prediction; and generating a confidence value for the unimodal prediction and the bimodal prediction.

公开(公告)号：US20230267600A1

公开(公告)日：2023-08-24

申请号：US17728882

申请日：2022-04-25

Applicant: Samsung Display Co., Ltd.

Inventor： Shuhui Qu ,  Qisen Cheng ,  Janghwan Lee

IPC: G06T7/00 ,  G06N3/04

CPC classification number: G06T7/001 ,  G06N3/0454 ,  G06N3/0481 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: A system including: a memory, an encoder, a decoder, and a processor, the processor being connected to the memory, the encoder, and the decoder. The system is configured to: receive, at the encoder, an input image, divide, by the encoder, the input image into a plurality of image patches, select, by the encoder, codes corresponding to the plurality of image patches of the input image, from a codebook including the codes. The system is further configured to determine, by the encoder, an assigned code matrix including the codes corresponding to the plurality of image patches of the input image, receive, by the decoder, the assigned code matrix from the encoder. The system is further configured to generate, by the decoder, a reconstructed image based on the assigned code matrix.