P‐235: Late‐News Poster: Improving Automated Inspection and Repair Performance in Display Manufacturing through Diffusion‐based Generative AI
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| Formato: | Artículo Open Access |
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Wiley
2025
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| _version_ | 1867019059784056832 |
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| author | Seung-Gi Kim Eun-Chul Ko Haneul Kim DongGon Yoo SangRock Son |
| author_facet | Seung-Gi Kim Eun-Chul Ko Haneul Kim DongGon Yoo SangRock Son Seung-Gi Kim Eun-Chul Ko Haneul Kim DongGon Yoo SangRock Son |
| collection | Wiley Open Access |
| contents | P‐235: Late‐News Poster: Improving Automated Inspection and Repair Performance in Display Manufacturing through Diffusion‐based Generative AI Seung-Gi Kim Eun-Chul Ko Haneul Kim DongGon Yoo SangRock Son SID Symposium Digest of Technical Papers This study presents a diffusion‐based generative AI approach to address dataset imbalances in display manufacturing automation. By generating realistic synthetic data for defects and repair failures, we achieved high‐performance classification AI and detection AI, enabling automation previously reliant on human operators. The proposed method demonstrates the potential of diffusion models to expand automation in manufacturing processes utilizing computer vision. 10.1002/sdtp.18513 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| doi_str_mv | 10.1002/sdtp.18513 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_sdtp_18513 |
| institution | Wiley Open Access |
| license_str_mv | http://onlinelibrary.wiley.com/termsAndConditions#vor |
| publishDate | 2025 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | P‐235: Late‐News Poster: Improving Automated Inspection and Repair Performance in Display Manufacturing through Diffusion‐based Generative AI Seung-Gi Kim Eun-Chul Ko Haneul Kim DongGon Yoo SangRock Son SID Symposium Digest of Technical Papers P‐235: Late‐News Poster: Improving Automated Inspection and Repair Performance in Display Manufacturing through Diffusion‐based Generative AI Seung-Gi Kim Eun-Chul Ko Haneul Kim DongGon Yoo SangRock Son SID Symposium Digest of Technical Papers This study presents a diffusion‐based generative AI approach to address dataset imbalances in display manufacturing automation. By generating realistic synthetic data for defects and repair failures, we achieved high‐performance classification AI and detection AI, enabling automation previously reliant on human operators. The proposed method demonstrates the potential of diffusion models to expand automation in manufacturing processes utilizing computer vision. 10.1002/sdtp.18513 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| title | P‐235: Late‐News Poster: Improving Automated Inspection and Repair Performance in Display Manufacturing through Diffusion‐based Generative AI |
| topic | SID Symposium Digest of Technical Papers |
| url | https://sid.onlinelibrary.wiley.com/doi/10.1002/sdtp.18513 |