91‐3: <i>Late‐News Paper:</i> Unsupervised Anomaly Detection Using Diffusion Trend Analysis for Display Inspection

Reconstruction‐based anomaly detection via denoising diffusion model has limitations in determining appropriate noise parameters that can degrade anomalies while preserving normal characteristics. Also, normal regions can fluctuate considerably during reconstruction, resulting in false detection. In this paper, we propose a method to detect anomalies by analysis of reconstruction trend depending on the degree of degradation, effectively solving the both problems that impede practical application in display inspection.

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Publication Details

Journal
SID Symposium Digest of Technical Papers
Published
2025-06-01
DOI
https://doi.org/10.1002/sdtp.18412
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

91‐3: Late‐News Paper: Unsupervised Anomaly Detection Using Diffusion Trend Analysis for Display Inspection

SID Symposium Digest of Technical Papers
Geochemistry and Geologic Mapping
article

91‐3: Late‐News Paper: Unsupervised Anomaly Detection Using Diffusion Trend Analysis for Display Inspection

article en

Abstract

Reconstruction‐based anomaly detection via denoising diffusion model has limitations in determining appropriate noise parameters that can degrade anomalies while preserving normal characteristics. Also, normal regions can fluctuate considerably during reconstruction, resulting in false detection. In this paper, we propose a method to detect anomalies by analysis of reconstruction trend depending on the degree of degradation, effectively solving the both problems that impede practical application in display inspection.

SID Symposium Digest of Technical PapersVol. 56(1)
Samsung (South Korea) (KR), Stanford University (US)
Sustainable cities and communities
Openalex Percentile: Top 69%
Geochemistry and Geologic Mapping
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