Global Template Projection and Matching Method for Training-Free Analysis of Delayered IC Images
Global Template Projection and Matching Method for Training-Free Analysis of Delayered IC Images
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用于延迟 IC 图像免训练分析的全局模板投影和匹配方法
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Kar
中科院分区：
文献类型：
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作者：
Deruo Cheng;Yiqiong Shi;Tong Lin;B. Gwee;Kar
模式识别算法近来已被用于分层IC图像的自动分析，即电路元件的检测。现有的基于训练的方法的广泛实验受到繁重的数据标记，昂贵的模型训练或长处理时间的阻碍。在本文中，我们提出了一个全球模板投影和匹配（GTPM）的方法，不需要训练和最小量的数据标记的电路元件检测。我们提出的GTPM方法实现了更高或相当的准确性报告的方法，同时计算效率更高。
Pattern recognition algorithms have recently been pursued for automatic analysis of delayered IC images, i.e. the detection of circuit components. Wide experimentation on the existing training-based approaches are hampered by heavy data labeling, expensive model training, or long processing time. In this paper, we propose a global template projection and matching (GTPM) method that requires no training and a minimal amount of data labeling for circuit component detection. Our proposed GTPM method achieves a higher or comparable accuracy as the reported approaches while being more computationally efficient.