公开(公告)号：US20250166266A1

公开(公告)日：2025-05-22

申请号：US18949390

申请日：2024-11-15

Applicant: Samsung Display Co., Ltd.

Inventor： Zhihong Pan ,  Rahul Shenoy ,  Kaushik Balakrishnan ,  Qisen Cheng ,  Janghwan Lee

IPC: G06T11/60 ,  G06T5/60 ,  G06T5/70 ,  G06T7/00

Abstract: A system and a method are disclosed for defect image generation using diffusion model sampling. The method includes generating, by a processor via a diffusion model, a noisy image from a defect-free image, generating, by the processor via the diffusion model, a sampled defect image and a sampled defect-free image from the noisy image, generating, by the processor, a mask based on the sampled defect image and the sampled defect-free image, generating, by the processor, a synthetic defect image by generating an additional sampled defect image based on the noisy image and the mask, and transmitting, by the processor, the synthetic defect image.

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：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.