Title:Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Title : Unified CNN-LSTM for keyhole status prediction in PAW based on spatial-temporal features
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Affiliation of Author(s):材料科学与工程学院
Title of Paper:Unified CNN-LSTM for keyhole status prediction in PAW based on spatial-temporal features
Journal:Expert Systems with Applications
First Author:周方正
Document Code:1712641353000992770
Volume:237
Number of Words:5000
Translation or Not:no
Date of Publication:2024-03-01
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