Classification of lines, spaces, and edges of resist patterns in scanning electron microscopy images using unsupervised machine learning

As key steps of lithography, the development of resist materials and the exploration of new materials are important to meet market demands from the semiconductor industry. During the development, resist materials are usually evaluated by the information extracted from their scanning electron microsc...

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Veröffentlicht in:	Japanese Journal of Applied Physics 2022-05, Vol.61 (5), p.56505
Hauptverfasser:	Jin, Yuqing, Kozawa, Takahiro
Format:	Artikel
Sprache:	eng
Schlagworte:	Centroids Cluster analysis Clustering EB lithography EUV lithography Image classification Industrial development Information retrieval Machine learning resist image Scanning electron microscopy SEM images Substrates Unsupervised learning unsupervised machine learning
Online-Zugang:	Volltext
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