Swin–UNet++: A Nested Swin Transformer Architecture for Location Identification and Morphology Segmentation of Dimples on 2.25Cr1Mo0.25V Fractured Surface

Swin–UNet++: A Nested Swin Transformer Architecture for Location Identification and Morphology Segmentation of Dimples on 2.25Cr1Mo0.25V Fractured Surface

The precise identification of micro-features on 2.25Cr1Mo0.25V steel is of great significance for understanding the mechanism of hydrogen embrittlement (HE) and evaluating the alloy’s properties of HE resistance. Presently, the convolution neural network (CNN) of deep learning is widely applied in t...

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Bibliographic Details
Main Authors: Pan Liu, Yan Song, Mengyu Chai, Zelin Han, Yu Zhang
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Materials
Subjects:
artificial intelligence
dimple
ductile fracture
fractured surface
semantic segmentation
transformer
Online Access:https://www.mdpi.com/1996-1944/14/24/7504

Internet

https://www.mdpi.com/1996-1944/14/24/7504

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