搜索资源列表
BagOfWordsDEMO
- BAG OF WORDS算法应用于图片分类。图像特征用sift算法描述,分类机利用了libsvm方法。-BAG OF WORDS algorithm is applied to image classification. Image features using sift algorithm descr iption, classification machine utilizes libsvm method.
image-sentiment-analysis
- 图片情感分析模型,基于卷积神经网络,以颜色特征为依据进行情感分类,图片情感极性分为积极和消极两类。(The model can extract the hue, brightness, contrast and other information from a picture to represent the emotional polarity of the image. The image sentiment analysis model is using convolution neura
BP网络图像分类
- 识别图像中道路,建筑,基于BP神经网络,里面有图片(Identify roads, buildings, etc in images)
GoogleNet_MATLAB-master
- GoogleNet 卷积神经网络 图片分类 分类精度高 网络结构深(GoogleNet convolution neural network image classification, high classification accuracy, network structure is deep)
label_image
- 基于TensorFlow框架,实现对图片分类(Achieve classification of pictures)
re
- 可用于 caffe环境,适于初学者,包括了五个类别,每个类别100张图片 ,有公交 恐龙 鲜花 马 大象。(it can be used in caffe environment. suitable for new learner)
图片的分类处理
- The program can be used to classify photos into two parts
PyConvNet-master
- python实现卷积网络,实现简单的图片分类的功能(Implementation of coiler network with Python)
Sig_fig
- 分类两组图片,利用了 PIL 和 Tensorflow 进行训练(classify two kinds of photograph)
Classification
- 一个C++程序能够实现对车辆图片的分类代码(To achieve the classification of vehicle picture code)
knn
- 人工智能导论课作业,水杯图片的分类,knn方法实现(Homework of AI. classify images of cups and bottles. Using knn)
svm
- 人工智能导论作业,用SVM方法实现的水杯图片分类,并生成loss的下降趋势图(Homework of AI. Using SVM to classify images of cups and bottles.)
softmax
- 人工智能导论作业,用softmax方法实现的水杯图片分类,可扩展到其他分类任务(Homework of AI. Classify images of cups using softmax. Can be used in other tasks.)
svmtrain
- 基于支持向量机的对指定多个包含特征的训练集图片,包含label信息。训练后,可对于相同格式的图片进行分类。(A training set image containing multiple features is included in the support vector machine (SVM), which contains label information. After training, the pictures in the same format can be classifi
classification
- 实现两类图片分类,针对的是X光图片进行分类。(image classification)
mnist实验
- 包含训练用的图片数据包,python源代码,mnist实验,深度学习,进行图片分类(mnist experiment.python code.deep learning.picture classification,etc.)
风景与建筑图片的分类——支持向量机的方法
- 风景与建筑图片的分类——支持向量机的方法(Classification of landscape and architectural pictures -- Method of support vector machine)
matlab实现LeNet
- 卷积神经网络LeNet代码,可实现图片分类(Convolution neural network code)
人脸检测OPENCV
- 使用VS2013编写+OPENCV2.49,能够读取图片并识别人脸,采用 分类器制作,调试通过,也可以改为摄像头
cifar10_tutorial
- 非常适合入门的一个深度学习图片分类例程!(Very suitable for beginners to learn a deep picture classification routines!)