Deep learning based automated quantification of powders used in additive manufacturing

This study proposes a novel deep learning technique for efficient powder morphology characterization, crucial for successful additive manufacturing. The method segments powder particles in microscopy images using Pix2Pix image translation model, enabling precise quantification of size distribution a...

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Bibliographic Details
Main Authors:	K.V. Mani Krishna, A. Anantatamukala, Narendra B. Dahotre
Format:	Article
Language:	English
Published:	Elsevier 2024-12-01
Series:	Additive Manufacturing Letters
Subjects:	Machine learning Powder size distribution CNN Quantification Generative adversarial networks
Online Access:	http://www.sciencedirect.com/science/article/pii/S2772369024000495
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Deep learning based automated quantification of powders used in additive manufacturing

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