搜索资源列表
NNPic
- 对图像的亮度分布曲线进行人工智能学习，并分类的多隐含层的BP神经网络(The BP neural network of the multi hidden layer of artificial intelligence learning for the brightness distribution curve of the image and the classification of the multi hidden layer)
tensorflow-CNN-CIFAR-10-master
- CNN实现图像数据的分类，有数据库下载代码(CNN implements the classification of image data, and there is a database download code)
wnit
- 支持向量机,用于分类,Classify using (a very simple implementation of) t()
1324802
- 用支持向量机(SVM)实现分类与函数回归的源代码,内有实例,依湖芦画瓢即可,()
CNN_matlab
- 卷积神经网络（CNN）是一种深度学习方法，它可以对图像进行识别和特征分类等优点。(The convolution neural network (CNN) is a deep learning method which can identify and characterize the image.)
Fisher字典学习
- 基于稀疏表示的高光谱图像分类的Fisher字典学习方法matlab代码(Hypersynthetic image classification based on sparse representation in Fisher dictionary learning matlab code.)
grabcut
- 机器学习图像分类中，采用Grabcut分割图像获得ROI(segmentation method , get the ROI)
get feature
- 在机器学习图像分类的过程中，对ROI进行形状和纹理特征提取(exact the shape and texture features of ROI)
att_faces
- 实现图像分类中的传统方法，主要有特征提取模块，还有分类模块，其中该算法将其整合实现了端到端的训练和测试(image classification)
NMF
- 使用NMF和KNN分类器实现对高维图像的降维处理(use NMF and KNN for high dimensional image)
MSTAR官方数据集
- 用于SAR图像识别与分类的官方MSTAR图像集，百度云链接，永久有效，2GB。(Official MSTAR image set for SAR image recognition and classification, Baidu cloud link, permanently valid, 2GB.)
zuoye
- 对图像进行分割，同时根据贝叶斯分类准则，对图像进行准确分类，可以分别识别各种图形的形状(The image is segmented, and the image is accurately classified according to Bias classification rule, and all kinds of shapes can be identified separately.)
规则图像特征提取
- 运用matlab规则图像特征提取分析，分类(Feature extraction of regular image)
Demo_Broadlearning_MNIST
- 宽度学习是最近比较热的分类器，可用于图像分类等应用(image classification Broad learning)
fisher
- 识别所给出图像与图像库中的图像进行比对识别分类(The recognition and classification of the image and the image in the image library are identified.)
fenlei
- 利用hog提取特征输入到svm分类器中，适用于新手(Using hog extraction feature input to svm classifier, suitable for novices)
CRF++-0.44.tar
- 条件随机场的c++实现，可用于文本标注、图像分类、分割等领域(conditional random field,CRF++ 0.44)
20171211留档
- 利用SVM对制备的样本进行三分类，对图像进行三角形匹配，模板匹配(SVM was used to classify the samples in three categories. Triangle matching and template matching were applied to the images.)
subareaFlevoland
- 极化SAR图像分类数据，Flevoland部分地区T3矩阵数据(Dataset for PolSAR image classification, T3 matrix of Flevoland subarea.)
CIFAR10
- 在CIFAR-10数据集上使用卷积神经网络进行图像分类(Image classification using convolution neural network on CIFAR-10 dataset)