论文标题
基于机器学习的亮度分析$μ$ LED阵列
Machine learning based luminance analysis of a $μ$LED array
论文作者
论文摘要
在过去的几年中，$μ$ LED阵列的开发获得了动力，因为它们结合了$μ$ LED的优势，例如高亮度和寿命，并与微分级结构相结合。为了开发，分析了单个$ $ $ LED的亮度和颜色的空间分析测量值，并分析了整个发光表面，因为它们对于视觉感知至关重要。但是，前者是测量和评估的时间很紧张，后者遭受了由非功能性$μ$ LED引起的干扰。本文提出了一种使用无监督的机器学习进行单个测量进行两项分析的方法。结果表明，可以实现$μ$ LED的宝贵重建以及更准确的特征$ $ $ LED阵列。
In the past years, the development of $μ$LED arrays gained momentum since they combine the advantages of $μ$LEDs, such as high brightness and longevity, with a high resolution of a micro-scaled structure. For the development, spatially resolved measurements of luminance and color of single $μ$LEDs and the entire light-emitting surface are analyzed as they are crucial for the visual perception. However, the former is time intense in measurement and evaluation, and the latter suffers from interference caused by nonfunctional $μ$LEDs. This paper presents a method to perform both analyzes with a single measurement using unsupervised machine learning. The results suggest that a precious reconstruction of the $μ$LEDs and a more accurate characterization $μ$LED arrays can be achieved.
