裂缝检测技术-基于图像处理
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– 用于裂缝分类
用于裂缝分类
- Concrete Crack Images for Classification
像素值:227×227
数量:40000张(20000negative+20000postive)
引用该数据集的论文:
“Automatic crack distress classification from concrete surface images using a novel deep-width network architecture”
- crack-detection
像素值:224×224
数量:6077张( 4856 training pictures and 1213 test pictures)
引用该数据集的论文:
“Automated Bridge Crack Detection Using Convolutional Neural Networks”
Paper link:https://www.mdpi.com/2076-3417/9/14/2867
[1]Xu H, Su X, Wang Y, et al. Automatic Bridge Crack Detection Using a Convolutional Neural Network[J]. Applied Sciences, 2019, 9(14): 2867.
[2]Li Liang-Fu, Ma Wei-Fei, Li Li, Lu Cheng. Research on detection algorithm for bridge cracks based on deep learning. Acta Automatica Sinica, 2018
- crackdataset-voc
VoC格式数据集
数量:3000左右
- ConcreteDataset
SDNET2018
- Historical Building Cracks
- multi_classifier_data
数据集下载链接请私信或留言
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Original: https://blog.csdn.net/weixin_42535423/article/details/115141295
Author: 香博士
Title: 裂缝检测专题(3)裂缝数据集dataset总结1-分类
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