In Situ Capture of High-Temperature Precipitate Phases in Ti-48Al-2Cr-2Nb Alloy Using Convolutional Neural Networks

In Situ Capture of High-Temperature Precipitate Phases in Ti-48Al-2Cr-2Nb Alloy Using Convolutional Neural Networks

TiAl intermetallic alloy is a crucial high-performance material, and its microstructure evolution at high temperatures is closely related to the process parameters. Observing the lamellar structure is key to exploring growth kinetics, and the feature extraction of precipitate phases can provide an e...

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Bibliographic Details
Main Authors: Xiaolei Li, Chuanqing Huang, Sen Zhao, Linlin Cui, Shirui Guo, Bo Zheng, Yinghao Cui, Yongqian Chen, Yue Zhao, Lujun Cui, Chunjie Xu
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Crystals
Subjects:
γ lamellar microstructure
rotated box
object detection
YOLOv5
computer vision
Online Access:https://www.mdpi.com/2073-4352/15/6/577
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