搜索资源列表
Version 1.0
- 这些代码主要是IDL语言源码，主要功能：初始化ENVI,定标,大气校正,融合,镶嵌,裁剪,分类(监督+非监督),面向对象特征提取,结束ENVI(These codes are mainly IDL language source code, the main functions: initialization, ENVI, calibration, atmospheric correction, fusion, mosaic, cutting, classification (supervisi
2016_GAN_Matlab-master
- GAN的matlab版本，用于图像分类和生成(The matlab version of GAN is used for image classification and generation)
SVM
- 通过HOG获取特征，用SVM对图像进行分类。(The feature is acquired by HOG, and the image is classified by SVM.)
pointDraw
- 在matlab中根据不同类型点画在图像中的程序(In MATLAB according to different types of points in the image of the program)
matconvnet-1.0-beta19.tar
- matlab实现CNN卷积神经网络，进行图像分类。(We can realize neural network with matlab, which will complete the classification of the image.)
Colorhist_Libsvm_dem
- 随着科学技术的飞速发展，机器学习与人工智能技术的不断创新，人们对特定信息检索的需求逐渐增加，使得如何对资源进行合理有效的分类成为一个关键问题。近几年来，基于内容的图像分类的研究焦点主要集中在自然图像的场景分类和物体分类两个方面，大多采用有监督学习方法，通过对底层特征建模和中间语义分析来实现分类。 本文基于Libsvm的图像分类研究及实现，主要针对的是物体分类这一方面，选用了五类水果作为分类研究的对象。对图像进行分类的大体步骤主要包括采集图像样本（主要从Web上获取）、图像预处理（如截成大小一致
kernelBP_chol
- 针对图像的基于核置信传播的分类器，具有收敛速度快，精度高的优点。(This is a sample code for Kernel Belief Propagation Classifier for images.)
CLBC
- clbc,用于图像分类，是Yang Zhao和 De-Shuang Huang的学术论文仿真(Clbc, used in image classification, is the academic paper simulation of Yang Zhao and De-Shuang Huang)
RSC
- 只要是使用稀疏表示方法进行的图像分类，非常有用！(It is useful as long as it is an image classification using the sparse representation method!)
PCA-SVM-master
- PCA/SVM算法实现图像分类，分类准确率可到达90%(Image classification by PCA/SVM algorithm)
160132
- c语言源码——基本遗传学习分类系统 基本遗传算法的源码()
9934046
- zoj的题型分类,以及部分题目的AC代码,对于acm的新手来说是个很好的参考！！CHM格式()
21855762
- svmLight 分类器,使用方便,有原代码可扩充算法,()
example_knn(降维)
- knn降维算法用于图像分类，将所给样本遥感图像按照要求进行分类(KNN dimensionality reduction algorithm for image classification)
a
- 对图像分类去燥，语音消除多余的噪声，达到较好的效果(The image classification is dryness, and the voice eliminates the excess noise)
wlpabilitywindows
- SVDD的工具箱,对一类分类效果非常好,包括圆形和不规则形状的包络面,()
FeatureExtractionUsingAlexNetExample
- 本示例展示了怎样从一个预处理的卷积神经网络中提取特征，并用这些特征去训练一个图像分类器。(This example shows how to extract learned features from a pretrained convolutional neural network, and use those features to train an image classifier. Feature extraction is the easiest and fastest way use
FaceTools-master
- 本次作业使用的是汤晓鸥团队的DeepID第一代的网络，通过Caffe训练模型参数，经过LFW二分类得到人脸识别准确率。(This job is used by the Tang Xiaoou team's DeepID first generation network. Through the Caffe training model parameters, the accuracy of face recognition is obtained through the LFW two clas
遥感数字图像处理
- 较为系统地讲述了遥感数字图像处理必备的基础知识，遥感图像预处理、增强处理、遥感图像的监督分类和非监督分类等基本理论。(The basic knowledge of remote sensing digital image processing, the basic theory of remote sensing image preprocessing, enhancement processing, supervised classification and unsupervised clas
PaviaEMPSVM
- 利用形态学滤波结合SVM分类算法对高光谱图像进行分类(Using morphological filtering and SVM classification algorithm to classify hyperspectral images)