Synthetic-to-Real Composite Semantic Segmentation in Additive Manufacturing

The application of computer vision and machine learning methods for semantic segmentation of the structural elements of 3D-printed products in the field of additive manufacturing (AM) can improve real-time failure analysis systems and potentially reduce the number of defects by providing additional...

詳細記述

書誌詳細

出版年:	Journal of Manufacturing and Materials Processing
主要な著者:	Aliaksei Petsiuk, Harnoor Singh, Himanshu Dadhwal, Joshua M. Pearce
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2024-03-01
主題:	3D printing additive manufacturing g-code segmentation sim-to-real semantic segmentation synthetic data
オンライン･アクセス:	https://www.mdpi.com/2504-4494/8/2/66