Código QR (código de barras bidimensional)

Physics-Aligned Data Augmentation for Reliable Property Prediction in Direct Ink Writing Under Extreme Data Scarcity

Reliable property prediction in extrusion-based additive manufacturing remains challenging under extreme data scarcity (e.g., sample size of <50), particularly when experiments are constrained by designed studies such as Taguchi orthogonal arrays. In direct ink writing of lignocellulosic composites,...

ver descrição completa

Na minha lista:
Principais autores: Biva Gyawali, Pavan Akula, Kamran Alba, Vahid Nasir
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2026-03-01
coleção:Journal of Manufacturing and Materials Processing
Assuntos:
data-driven additive manufacturing
synthetic data augmentation
direct ink writing (DIW)
explainable machine learning
variational autoencoder
generative adversarial network (GAN)
Acesso em linha:https://www.mdpi.com/2504-4494/10/4/118
Tags: Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!

Registros relacionados