Porosity evaluation of additively manufactured components using deep learning-based ultrasonic nondestructive testing

Research output: Contribution to journal › Journal article › peer-review

Original language	Korean
Journal	INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY
State	Published - 2022.03.1

Cite this

TY - JOUR

T1 - Porosity evaluation of additively manufactured components using deep learning-based ultrasonic nondestructive testing

AU - Choi, Sungho

PY - 2022/3/1

Y1 - 2022/3/1

M3 - Journal article

JO - INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY

JF - INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY

ER -