资源列表
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- 该代码实现了曲线平滑，可以调用，符合初学者，简单易懂，供大家学习使用。-The code to achieve a smooth curve, you can call, in line with beginners, easy to understand, for everyone to learn to use.
cvpr16_MSTSaliency-mex
- 基于最小生成树的目标显著度探测，2016cvpr-Target based on the minimum spanning tree of a significant degree of detection, 2016cvpr
distrubution
- 经过分水岭算法、与形态学算法结合后，对颗粒分布进行统计，并画出晶粒分布直方图直方图。-After the watershed algorithm, later combined with morphology algorithm, the statistical particle size distribution, grain size distribution histogram and draw a histogram.
MyCom
- 通过编辑QT数据采集界面并进行波形显示,实时显示波形曲线-QT interface by editing the data acquisition and waveform display
DIPDemo
- 《数字图像处理与计算机视觉 Vc++与matlab实现》一书的源码，是学习图像处理，自己动手编程的最好的参考资料。- Digital image processing and computer vision- Visual C++ and matlab implementation, a book of the source, is to learn image processing, their own hands-on programming the best reference.
second_edition_code
- 《opencv2计算机视觉编程手册第二版》一书的配套源码。-These file contains material supporting the cookbook:Computer Vision Programming using the OpenCV Library. Second Edition by Robert Laganiere, Packt Publishing, 2013.
libsvm-3.22
- libsvm3-22 svm库 比较新。用起来很好。 LIBSVM是台湾大学林智仁(LinChih-Jen)教授等开发设计的一个简单、易于使用和快速有效的SVM模式识别与回归的软件包，他不但提供了编译好的可在Windows系列系统的执行文件，还提供了源代码，方便改进、修改以及在其它操作系统上应用。-libsvm3-22 svm repository relatively new. Use them well. LIBSVM is a simple, easy to use and fas
similaritymeasure
- 在对图像进行识别和分类过程中，相似性测量可以作为一种判别策略，目的是刻画图像之间的本质特性。-In the image recognition and classification process, the similarity measure can be used as a discriminating strategy aimed portray the essential characteristics of images.
ImageProcess
- 用c++编写的一个具有图像处理功能的GUI界面，四个功能，界面简洁漂亮。希望对有需要的朋友有所帮助。-A written in c++ GUI interface with image processing functions, four function, the interface is concise and beautiful. Hope to have a friend needs help.
69491709Training-code-for-SRCNN
- 先用训练样本对模型SRCNN进行训练，然后使用测试样本测试模型的有效性-First with the effectiveness of the model SRCNN training samples for training, and then use the test sample test model
53607888mnistclassify_DBN
- 目前深度学习已经得到研究者的广泛关注，在这里深信度网络被用于手写字符的识别，得到非常好的分类精度。-Currently deep learning has been much attention, here we are convinced of the network is used to identify handwritten characters, get very good classification accuracy.
CNN-pooling-strategy
- 基于卷积层和池化层的卷积深度网络被执行，该框架可以有效地识别灰度图像，彩色图像和高光谱图像。- Convolution deep network based on convolution layer and pooling layer is performed, the framework can effectively identify grayscale images, color images and hyperspectral images.