登录
首页 » Python » DeepCrack

DeepCrack

于 2021-04-09 发布
0 250
下载积分: 1 下载次数: 0

代码说明:

说明:  裂纹是典型的线结构,在许多计算机视觉应用中都很有趣。在实际应用中,路面裂缝等许多裂缝连续性差、对比度低,给利用低层特征进行基于图像的裂缝检测带来了很大的挑战。在本文中,我们提出了深度裂纹——一个端到端可训练的深度卷积神经网络,通过学习用于裂纹表示的高级特征来自动检测裂纹。该方法将在层次卷积阶段学习到的多尺度深度卷积特征融合在一起,以获取线路结构。更详细的表示在大比例尺的feature maps中进行,更全面的表示在小比例尺的feature maps中进行。我们在SegNet的编码器解码器架构上构建深度裂纹网,并对在相同尺度下在编码器网络和解码器网络中生成的卷积特征进行配对融合。(Cracks are typical line structures that are of interest in many computer-vision applications. In practice, many cracks, e.g., pavement cracks, show poor continuity and low contrast, which bring great challenges to image-based crack detection by using low-level features. In this paper, we propose DeepCrack---an end-to-end trainable deep convolutional neural network for automatic crack detection by learning high-level features for crack representation. In this method, multi-scale deep convolutional features learned at hierarchical convolutional stages are fused together to capture the line structures. More detailed representations are made in larger scale feature maps and more holistic representations are made in smaller scale feature maps. We build DeepCrack net on the encoder decoder architecture of SegNet and pairwisely fuse the convolutional features generated in the encoder network and in the decoder network at the same scale.)

文件列表:

DeepCrack, 0 , 2020-10-17
DeepCrack\.git, 0 , 2020-10-17
DeepCrack\.git\HEAD, 23 , 2020-10-17
DeepCrack\.git\config, 303 , 2020-10-17
DeepCrack\.git\description, 73 , 2020-10-17
DeepCrack\.git\hooks, 0 , 2020-10-17
DeepCrack\.git\hooks\applypatch-msg.sample, 478 , 2020-10-17
DeepCrack\.git\hooks\commit-msg.sample, 896 , 2020-10-17
DeepCrack\.git\hooks\fsmonitor-watchman.sample, 3327 , 2020-10-17
DeepCrack\.git\hooks\post-update.sample, 189 , 2020-10-17
DeepCrack\.git\hooks\pre-applypatch.sample, 424 , 2020-10-17
DeepCrack\.git\hooks\pre-commit.sample, 1638 , 2020-10-17
DeepCrack\.git\hooks\pre-push.sample, 1348 , 2020-10-17
DeepCrack\.git\hooks\pre-rebase.sample, 4898 , 2020-10-17
DeepCrack\.git\hooks\pre-receive.sample, 544 , 2020-10-17
DeepCrack\.git\hooks\prepare-commit-msg.sample, 1492 , 2020-10-17
DeepCrack\.git\hooks\update.sample, 3610 , 2020-10-17
DeepCrack\.git\index, 3375 , 2020-10-17
DeepCrack\.git\info, 0 , 2020-10-17
DeepCrack\.git\info\exclude, 240 , 2020-10-17
DeepCrack\.git\logs, 0 , 2020-10-17
DeepCrack\.git\logs\HEAD, 186 , 2020-10-17
DeepCrack\.git\logs\refs, 0 , 2020-10-17
DeepCrack\.git\logs\refs\heads, 0 , 2020-10-17
DeepCrack\.git\logs\refs\heads\master, 186 , 2020-10-17
DeepCrack\.git\logs\refs\remotes, 0 , 2020-10-17
DeepCrack\.git\logs\refs\remotes\origin, 0 , 2020-10-17
DeepCrack\.git\logs\refs\remotes\origin\HEAD, 186 , 2020-10-17
DeepCrack\.git\objects, 0 , 2020-10-17
DeepCrack\.git\objects\info, 0 , 2020-10-28
DeepCrack\.git\objects\pack, 0 , 2020-10-17
DeepCrack\.git\objects\pack\pack-34efcbab4f1f2cc4ba308e8e137e64429842d058.idx, 8156 , 2020-10-17
DeepCrack\.git\objects\pack\pack-34efcbab4f1f2cc4ba308e8e137e64429842d058.pack, 4746282 , 2020-10-17
DeepCrack\.git\packed-refs, 321 , 2020-10-17
DeepCrack\.git\refs, 0 , 2020-10-17
DeepCrack\.git\refs\heads, 0 , 2020-10-17
DeepCrack\.git\refs\heads\master, 41 , 2020-10-17
DeepCrack\.git\refs\remotes, 0 , 2020-10-17
DeepCrack\.git\refs\remotes\origin, 0 , 2020-10-17
DeepCrack\.git\refs\remotes\origin\HEAD, 32 , 2020-10-17
DeepCrack\.git\refs\tags, 0 , 2020-10-28
DeepCrack\DeepCrack_ Learning Hierarchical Convolutional_ Features for Crack Detection.pdf, 10976720 , 2020-10-20
DeepCrack\README.md, 8518 , 2020-10-17
DeepCrack\codes, 0 , 2020-10-17
DeepCrack\codes\checkpoints, 0 , 2020-10-17
DeepCrack\codes\checkpoints\111, 2 , 2020-10-17
DeepCrack\codes\config.py, 1662 , 2020-10-17
DeepCrack\codes\data, 0 , 2020-10-17
DeepCrack\codes\data\111, 2 , 2020-10-17
DeepCrack\codes\data\augmentation.py, 2824 , 2020-10-17
DeepCrack\codes\data\dataset.py, 1996 , 2020-10-17
DeepCrack\codes\data\train_example.txt, 9678 , 2020-10-17
DeepCrack\codes\data\val_example.txt, 21470 , 2020-10-17
DeepCrack\codes\model, 0 , 2020-10-17
DeepCrack\codes\model\111, 2 , 2020-10-17
DeepCrack\codes\model\deepcrack.py, 4885 , 2020-10-17
DeepCrack\codes\test.py, 2019 , 2020-10-17
DeepCrack\codes\tools, 0 , 2020-10-17
DeepCrack\codes\tools\111, 2 , 2020-10-17
DeepCrack\codes\tools\checkpointer.py, 5678 , 2020-10-17
DeepCrack\codes\tools\paths.py, 2189 , 2020-10-17
DeepCrack\codes\tools\visdom.py, 3931 , 2020-10-17
DeepCrack\codes\train.py, 10309 , 2020-10-17
DeepCrack\codes\trainer.py, 4728 , 2020-10-17
DeepCrack\figures, 0 , 2020-10-17
DeepCrack\figures\1000.png, 334581 , 2020-10-17
DeepCrack\figures\1014.png, 334119 , 2020-10-17
DeepCrack\figures\1022.png, 276344 , 2020-10-17
DeepCrack\figures\1042.png, 222428 , 2020-10-17
DeepCrack\figures\1045.png, 220442 , 2020-10-17
DeepCrack\figures\1065.png, 216662 , 2020-10-17
DeepCrack\figures\1095.png, 307001 , 2020-10-17
DeepCrack\figures\1096.png, 276440 , 2020-10-17
DeepCrack\figures\6192.jpg, 233477 , 2020-10-17
DeepCrack\figures\6207.jpg, 219375 , 2020-10-17
DeepCrack\figures\6264.jpg, 212356 , 2020-10-17
DeepCrack\figures\6328.jpg, 216801 , 2020-10-17
DeepCrack\figures\6750.jpg, 185073 , 2020-10-17
DeepCrack\figures\DSCN6428.JPG, 250994 , 2020-10-17
DeepCrack\figures\deepcrack-compare1.png, 484981 , 2020-10-17
DeepCrack\figures\deepcrack-compare2.png, 97060 , 2020-10-17
DeepCrack\figures\deepcrack-compare3.png, 97722 , 2020-10-17
DeepCrack\figures\fig, 2 , 2020-10-17
DeepCrack\figures\intro.png, 437941 , 2020-10-17
DeepCrack\figures\network.png, 115374 , 2020-10-17

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • 三维多智能体仿真再现3d-多智能体
    展现了三维多智能体仿真再现,实现了多智能体协同一致性。(The simulation representation of 3d multi-agent is presented and the multi-agent couniformity is realized.)
    2020-11-16 15:39:40下载
    积分:1
  • Book_253919STEWARDESS--265877
    源码Book_253919STEWARDESS 265877是一个不错的源码,用来学习参考会是一个不错的选择(Source Book_253919STEWARDESS- 265877 is a good source, used to study the reference would be a good choice)
    2017-02-26 12:24:57下载
    积分:1
  • 捷联惯导及组合导航研究
    本文对捷联惯导系统(sINS)及其与全球定位系统(GPS)的组合导航系统进行 了研究。首先对实现S取S的初始对准及姿态矩阵计算等关键技术进行了系统研究。 在仿真的基础上进行了实际捷联惯导系统的系统研制,针对陀螺漂移补偿等关键算法 开展深入研究,实验结果表明经过补偿解算后,整个捷联惯导系统导航参数的解算精 度大大提高。在实现SINS的基础土,研究了SINS与GPS(The strapdown inertial navigation system (sINS) and global positioning system (GPS) of the integrated navigation system Study. Firstly, the key technology of implementing S S in the initial alignment and attitude matrix calculation were studied. On the basis of simulation of the actual development of the system of strapdown inertial navigation system, aiming at the key algorithm of gyro drift compensation The research results indicated that the compensation calculation, the strapdown inertial navigation system navigation parameters calculation precision Greatly improved. In the foundation of soil SINS, SINS and GPS were studied)
    2020-09-23 21:27:56下载
    积分:1
  • 100-C-programmers-language
    C开发人员,初级面试100道题,可以多看看,有利于打开开发的门。(C developers, primary interview 100 questions, you can see more, to open the doors of development.)
    2016-04-04 21:19:41下载
    积分:1
  • 脱机加脚本
    说明:  7.0版本以上UO脱机脚本,功能强大,非常好用,适合挂小号(Uo offline script above version 7.0, powerful, very easy to use, suitable for small size)
    2020-10-10 04:27:34下载
    积分:1
  • M
    说明:  Monitor the air quality in the indoor pool
    2017-10-30 12:33:09下载
    积分:1
  • CMS后台登录界面模版html静态页面
    说明:  CMS后台登录,方便操作,直观,自由娱乐方便聊天(CMS background login, easy to operate, intuitive, free entertainment and chat)
    2020-03-08 15:39:51下载
    积分:1
  • 802.11a wlan物理层仿真,里面有三个物理模型,均用MATLAB编写
    802.11a wlan物理层仿真,里面有三个物理模型,均用MATLAB编写-802.11a WLAN PHY There are*three* versions of the 802.11a physical layer model: R13/IEEE80211a.mdl: Requires R13 (MATLAB ) and Stateflow (for adaptive modulation control) R13/IEEE80211a_NoSF.mdl: Requires R13 (MATLAB), but does not require Stateflow. R13SP1/IEEE80211a.mdl Requires R13SP1 (MATLAB), but does not require Stateflow. This latest version also includes some bug fixes. All Simulink models require the Communications Blockset.
    2022-07-26 22:00:23下载
    积分:1
  • fusion
    用深度学习的方法,对多曝光的图像图像进行融合(Fusion of multi exposure image and image with deep learning method)
    2020-11-18 10:59:41下载
    积分:1
  • 本程序是在Ti的dm642上通过PCI和主机通信的测试程序
    本程序是在Ti的dm642上通过PCI和主机通信的测试程序-is in the process of Ti dm642 adopted PCI and host communications testing procedures
    2022-07-10 05:23:27下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载