Git Product home page Git Product logo

fscdd's Introduction

FSCDD

This is a large Facility Surface Crack Detection Dataset (FSCDD). FSCDD is composed of our laboratory dataset and those available on the Internet datasets.

The data set is primarily used to study for Facility Surface Cracks Detection, and is not allowed for commercial purposes; If you want to use this data set, you would to refer to the corresponding paper.The link is: https://pan.baidu.com/s/1bUqPjpi_YHEVsSq-dhDHKQ code: 08ia

Tunnel Crack:

@ARTICLE{8777129, author={Qu, Zhong and Chen, Si-Qi and Liu, Yu-Qin and Liu, Ling}, journal={IEEE Transactions on Intelligent Transportation Systems}, title={Linear Seam Elimination of Tunnel Crack Images Based on Statistical Specific Pixels Ratio and Adaptive Fragmented Segmentation}, year={2020}, volume={21}, number={9}, pages={3599-3607}, doi={10.1109/TITS.2019.2929483}}

CRACK500:

@inproceedings{zhang2016road, title={Road crack detection using deep convolutional neural network}, author={Zhang, Lei and Yang, Fan and Zhang, Yimin Daniel and Zhu, Ying Julie}, booktitle={Image Processing (ICIP), 2016 IEEE International Conference on}, pages={3708--3712}, year={2016}, organization={IEEE} }' .

@article{yang2019feature, title={Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection}, author={Yang, Fan and Zhang, Lei and Yu, Sijia and Prokhorov, Danil and Mei, Xue and Ling, Haibin}, journal={arXiv preprint arXiv:1901.06340}, year={2019} }

GAPs384:

@inproceedings{eisenbach2017how, title={How to Get Pavement Distress Detection Ready for Deep Learning? A Systematic Approach.}, author={Eisenbach, Markus and Stricker, Ronny and Seichter, Daniel and Amende, Karl and Debes, Klaus and Sesselmann, Maximilian and Ebersbach, Dirk and Stoeckert, Ulrike and Gross, Horst-Michael}, booktitle={International Joint Conference on Neural Networks (IJCNN)}, pages={2039--2047}, year={2017} }

CFD:

@article{shi2016automatic, title={Automatic road crack detection using random structured forests}, author={Shi, Yong and Cui, Limeng and Qi, Zhiquan and Meng, Fan and Chen, Zhensong}, journal={IEEE Transactions on Intelligent Transportation Systems}, volume={17}, number={12}, pages={3434--3445}, year={2016}, publisher={IEEE} }

AEL:

@article{amhaz2016automatic, title={Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection.}, author={Amhaz, Rabih and Chambon, Sylvie and Idier, J{'e}r{^o}me and Baltazart, Vincent} }

cracktree200:

@article{zou2012cracktree, title={CrackTree: Automatic crack detection from pavement images}, author={Zou, Qin and Cao, Yu and Li, Qingquan and Mao, Qingzhou and Wang, Song}, journal={Pattern Recognition Letters}, volume={33}, number={3}, pages={227--238}, year={2012}, publisher={Elsevier} }

李良福,马卫飞,李丽,陆铖.基于深度学习的桥梁裂缝检测算法研究[J].自动化学报,2019,45(09):1727-1742.

fscdd's People

Contributors

qiang-z avatar

Stargazers

盖亚 avatar  avatar litBAG avatar  avatar Jake Zhang avatar

Watchers

James Cloos avatar  avatar

fscdd's Issues

Sharing dataset on different repository

Hello, thank you for the great work. I would like to use this dataset for my work, but I cannot access the Baidu link listed. Is it possible to share the dataset on other repositories, such as Google Drive, DropBox, Zenodo, etc.? Thanks!

百度网盘问题

您的工作非常有价值,但是从百度网盘下载图片非常不方便,会提示图片数量过多
可否提供其他下载方式(如压缩包)呢?

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.