image classification

With the deep research of the polarimetric SAR ( Synthetic Aperture Radar) image classification, many supervised and unsupervised classification methods have been proposed one after another in recent years.

随着对极化SAR（synthetic Aperture Radar）图像分类研究的深入，近年来许多监督和非监督分类方法被相继提出。

This paper use the knowledge learnt from the source domain to help and speed up learning in the target domain through transfer learning, and implement a product image classification algorithm based on inductive transfer learning.

本文通过迁移学习的方法，利用从源领域中学习到的知识帮助并加快目标领域的学习，并在此基础上实现了一种基于归纳式迁移学习的商品图像分类算法。

Texture is one of the important distinctive feature that image shows in the local region. The effect of image classification relies heavily on the methods of extracting those textural features from images.

纹理是图像在局部区域内表现出来的一个重要特征，纹理特征提取方法的好坏，将直接影响图像分类的效果。

How to efficiently combine different textural features in order to get high performance is the study focus of the SAR image classification currently.

如何将不同纹理特征结合起来，以获得应用范围更广且分类效果更好的SAR图像分类方法，是当前SAR图像处理研究中的一个热点问题。

Remote sensing image classification based on hybrid learning vector quantization algorithm

基于混合学习矢量量化算法的遥感影像分类

Improving classification accuracy is always the focus for remote sensing image classification.

提高遥感图像分类精度一直是受到普遍关注的焦点问题.

Conventional remote sensing image classification methods are mostly based on Bayes subjective probability theory.

遥感图像分类是一项十分重要而且复杂的问题.

The texture image classification system is designed and realized based on texture spectrum and neural networks for applications in microimage analysis.

以显微图像分析为应用背景，设计并实现了基于改进的纹理谱方法提取特征和以神经网络作为分类器的纹理图像分类系统。

An improved hyperspectral remote sensing image classification method based on SOFM neural network

基于改进自组织竞争神经网络的高光谱图像分类

Design and Realization of texture image classification system

纹理图像分类系统的设计及实现

The Design of Medical Image Classification Based on Ensemble Leaning

基于集成学习方法的医学图像分类系统的设计

This paper deals with the techniques for improving image classification by extracting geometric attributes of objects.

利用地物的几何属性修正分类,以避免分类中的光谱混淆问题.

A Remote Sensing Image Classification Method Based on Evidence Theory and Neural Networks

一种基于证据理论与神经网络的遥感影像分类方法

Tee application of spatial information in image classification

空间信息在图象分类中的应用

A limitation in efficiently applying image classification is often represented by the spatial resolution of image.

影响遥感图像分类效果的主要因素之一是空间分辨率.

Unsupervised hyperspectral image classification method based on constrained linear discriminant analysis

基于约束线性判别分析的非监督高光谱影像分类方法

The paper proposes a novel probabilistic topic model for simultaneous image classification and annotation.

提出了同时做图像分类和标注的概率主题模型。

And SVM is a good choice for medical image classification.

而SVM是医学图像分类的良好选择。

I'm using PyTorch to build an image classification model.

我正在使用PyTorch构建一个图像分类模型。

Image classification and geo-information extraction is a fundamental process during the application of remote sensing technology.

在应用遥感技术获取地球资源信息的过程中,影像分类和地物信息解译是一项基础性工作.

Image classification is a process which simplifies the complex phenomenon to a small number of general categories. And it is an important way to extract useful information for the target recognition.

图像分类是将复杂的现象简化为少量的一般性类别的过程，是提取有用信息实现目标识别的重要途径。

By model optimization, this paper applies proposed DP-PMK to area of image classification, gives an empirical study using multi-class SVM method.

通过模型优化，将本文提出的DP-PMK算法应用于图像分类领域，给出了基于本文提出算法的支持向量机多分类实验结果。

Medical image classification plays a central role in automation of information system of hospitals.

医学图像的自动分类对于医院的信息自动化有重要的意义。

RS image classification and information derivation of mosquito habitats.

蚊媒孳生环境遥感分类和遥感信息提取研究。

In this paper, support vector machines are trained for natural image classification. The resulting image class models are incorporated into image retrieval system, so that the users can search natural images by classes.

该文以自然图像领域为例，使用支持向量机（SVM）学习自然图像的类别，学习到的模型用于自然图像分类和检索.贫验结果和模拟象符合的较好。

Traditional methods cannot meet the demands of high spatial resolution remote sensing image classification.

传统方法已然不能满足高空间分辨率遥感影像的分类要求。

Experimental results show that this new classifier can realize high quality unsupervised image classification, which outperforms the traditional K means classifier.

实验结果表明，该种分类器能很好地实现对纹理粗糙程度模式的无监督分类，其分类性能要明显好于传统的K均值分类器。

Knowledge based image classification approach supported by a GIS

GIS辅助下的基于知识的遥感影像分类方法研究&以土地覆盖/土地利用类型为例

Synthetic Aperture Radar ( SAR) image classification is a key technique of SAR image interpretation.

合成孔径雷达（SAR）图像分类是SAR图像解译的关键技术之一。

A feature extraction algorithm for remote sensing image classification based on class separability

基于类别可分离性的遥感图象特征提取方法