Paper
19 July 2024 Study of multilevel feature weighted fusion-based image classification method for silicon single crystal growth process
Ruidong Xie, Zheqi Zhang, Pei Zhu, Wenle Ma, Yingmin Yi
Author Affiliations +
Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132130K (2024) https://doi.org/10.1117/12.3035195
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China
Abstract
A multi-level feature weighted fusion based image classification method for silicon single crystal growth process has been proposed to address the issue of the long silicon single crystal pulling times at industrial sites, which prevents timely understanding of the crystal growth process. A multi-level feature weighted fusion method was employed to identify and classify the growth process of silicon single crystals. A Czochralski single crystal silicon growth process recognition system was then designed. A comparison of the experimental results obtained from this design with the traditional single image classification method clearly showed that using different levels of silicon single crystal image information simultaneously effectively improved the accuracy of silicon single crystal growth image classification.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Ruidong Xie, Zheqi Zhang, Pei Zhu, Wenle Ma, and Yingmin Yi "Study of multilevel feature weighted fusion-based image classification method for silicon single crystal growth process", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132130K (19 July 2024); https://doi.org/10.1117/12.3035195
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KEYWORDS
Crystals

Image processing

Feature fusion

Silicon

Image classification

Image fusion

Crystallography

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