{"title":"Vehicular Mini-LED backlight display inspection based on residual global context mechanism.","authors":"Guobao Zhao, Xi Zheng, Xiao Huang, Yijun Lu, Zhong Chen, Weijie Guo","doi":"10.1007/s12200-024-00140-4","DOIUrl":null,"url":null,"abstract":"<p><p>Mini-LED backlight has emerged as a promising technology for high performance LCDs, yet the massive detection of dead pixels and precise LEDs placement are constrained by the miniature scale of the Mini-LEDs. The high-resolution network (Hrnet) with mixed dilated convolution and dense upsampling convolution (MDC-DUC) module and a residual global context attention (RGCA) module has been proposed to detect the quality of vehicular Mini-LED backlights. The proposed model outperforms the baseline networks of Unet, Pspnet, Deeplabv3+, and Hrnet, with a mean intersection over union (Miou) of 86.91%. Furthermore, compared to the four baseline detection networks, our proposed model has a lower root-mean-square error (RMSE) when analyzing the position and defective count of Mini-LEDs in the prediction map by canny algorithm. This work incorporates deep learning to support production lines improve quality of Mini-LED backlights.</p>","PeriodicalId":12685,"journal":{"name":"Frontiers of Optoelectronics","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11519276/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers of Optoelectronics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s12200-024-00140-4","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Mini-LED backlight has emerged as a promising technology for high performance LCDs, yet the massive detection of dead pixels and precise LEDs placement are constrained by the miniature scale of the Mini-LEDs. The high-resolution network (Hrnet) with mixed dilated convolution and dense upsampling convolution (MDC-DUC) module and a residual global context attention (RGCA) module has been proposed to detect the quality of vehicular Mini-LED backlights. The proposed model outperforms the baseline networks of Unet, Pspnet, Deeplabv3+, and Hrnet, with a mean intersection over union (Miou) of 86.91%. Furthermore, compared to the four baseline detection networks, our proposed model has a lower root-mean-square error (RMSE) when analyzing the position and defective count of Mini-LEDs in the prediction map by canny algorithm. This work incorporates deep learning to support production lines improve quality of Mini-LED backlights.
微型 LED 背光已成为高性能液晶显示器的一项前景广阔的技术，但由于微型 LED 的微型尺寸，大量检测死像素和精确放置 LED 都受到限制。我们提出了带有混合扩张卷积和密集上采样卷积（MDC-DUC）模块和残差全局上下文注意（RGCA）模块的高分辨率网络（Hrnet），用于检测车辆微型 LED 背光的质量。所提出的模型优于 Unet、Pspnet、Deeplabv3+ 和 Hrnet 等基线网络，平均交集大于联合（Miou）为 86.91%。此外，与四个基线检测网络相比，我们提出的模型在使用 canny 算法分析预测图中 Mini-LED 的位置和缺陷数时，具有更低的均方根误差（RMSE）。这项工作结合了深度学习，以支持生产线提高 Mini-LED 背光的质量。
期刊介绍：
Frontiers of Optoelectronics seeks to provide a multidisciplinary forum for a broad mix of peer-reviewed academic papers in order to promote rapid communication and exchange between researchers in China and abroad. It introduces and reflects significant achievements being made in the field of photonics or optoelectronics. The topics include, but are not limited to, semiconductor optoelectronics, nano-photonics, information photonics, energy photonics, ultrafast photonics, biomedical photonics, nonlinear photonics, fiber optics, laser and terahertz technology and intelligent photonics. The journal publishes reviews, research articles, letters, comments, special issues and so on.
Frontiers of Optoelectronics especially encourages papers from new emerging and multidisciplinary areas, papers reflecting the international trends of research and development, and on special topics reporting progress made in the field of optoelectronics. All published papers will reflect the original thoughts of researchers and practitioners on basic theories, design and new technology in optoelectronics.
Frontiers of Optoelectronics is strictly peer-reviewed and only accepts original submissions in English. It is a fully OA journal and the APCs are covered by Higher Education Press and Huazhong University of Science and Technology.
● Presents the latest developments in optoelectronics and optics
● Emphasizes the latest developments of new optoelectronic materials, devices, systems and applications
● Covers industrial photonics, information photonics, biomedical photonics, energy photonics, laser and terahertz technology, and more
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