MixSegNet: A Novel Crack Segmentation Network Combining CNN and Transformer
In the domain of road inspection and structural health monitoring, precise crack identification and segmentation are essential for structural safety and disaster prediction. Traditional image processing technologies encounter difficulties in detecting cracks due to their morphological diversity and...
Saved in:
Main Authors: | Zhou, Yang, Ali, Raza, Mokhtar, Norrima, Harun, Sulaiman Wadi, Iwahashi, Masahiro |
---|---|
Format: | Article |
Published: |
Institute of Electrical and Electronics Engineers
2024
|
Subjects: | |
Online Access: | http://eprints.um.edu.my/47134/ https://doi.org/10.1109/ACCESS.2024.3438112 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Classification for Crop Pest on U-SegNet
by: Rani, A Anitha, et al.
Published: (2023) -
Automatic Polyp Segmentation in Colonoscopy Images Using Single Network Model: SegNet
by: Eu, Chin Yii, et al.
Published: (2022) -
Crack Segmentation Network using additive attention gate-CSN-II
by: Ali, Raza, et al.
Published: (2022) -
Failure analysis of driveshaft of Toyota SEG
by: Shuhaizal, Mohd Noor
Published: (2007) -
Real Time Eyeball Tracking via Derivative Dynamic Time Warping for Human-Machine Interface
by: Mokhtar, Norrima, et al.
Published: (2011)