Enhancing Materials Science through Computer Image Analysis and IQA Approaches

A. Piwowarczyk
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引用次数: 1

Abstract

Abstract. Computer image analysis allows for various object detection and classification as well as conducting measurements on microscope images. Technological development, including the application of artificial intelligence solutions, speeds up the classification of large data sets. In the context of image analysis, an essential issue is image quality assessment (IQA). Applying the tools of image analysis, or artificial intelligence, linked with the appropriate IQA approach reveals the opportunity to develop materials with better functional and technological properties more sustainably and effectively.
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通过计算机图像分析和IQA方法加强材料科学
摘要计算机图像分析允许对各种物体进行检测和分类,以及对显微镜图像进行测量。技术发展,包括人工智能解决方案的应用,加速了大型数据集的分类。在图像分析的背景下,一个关键问题是图像质量评估(IQA)。将图像分析工具或人工智能与适当的IQA方法相结合,揭示了开发具有更可持续和更有效的功能和技术性能的材料的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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