遗传算法

说明：  基于卷积神经网络的信号分类！识别率很高，速度很快(Signal classification based on convolutional neural network)

python代码实现的LOF算法代码(为什么会有人去做这么无聊的事情呢。。。）(Python code implements LOF algorithm code. (Why would anyone do such a boring thing?))

说明：  针对地理学、地理信息系统、遥感技术与应用等专业的技术人员，在使用ArcGIS软件绘图时，可以采用Python 中Arcpy 模块，实现批量处理。 针对栅格数据即遥感影像，在对图像进行分析时，如变化检测，土地覆盖类型提取等。这些都需要依据光谱特征对图像进行分类，并对分类后的结果进行标记。(For the technical personnel of geography, GIS, remote sensing technology and application, arcpy module in Python can be used to realize batch processing when drawing with ArcGIS software. For raster data, that is, remote sensing image, in the analysis of the image, such as change detection, land cover type extraction and so on. All of these need to classify the image according to the spectral characteristics and label the classified results.)

说明：  3DS kit extractor, used to extract .dbk and .dbf files

Keras是一个高层神经网络库， Keras由纯Python编写而成并基Tensorflow或Theano。 Keras 为支持快 速实验而生，能够把你的idea迅速转换为结果，如果你有如下需求，请选择Keras： 简易和快速的原型设计（keras具有高度模块化，极简，和可扩充特性） 支持CNN和RNN，或二者的结合 支持任意的链接方案（包括多输入和多输出训练） 无缝CPU和GPU切换(Keras is a high-level neural network library. Keras is written from pure Python and is based on Tensorflow or Theano. Keras support fast Quick experimentation can transform your idea into results quickly. If you have the following requirements, please choose Keras: Simple and fast prototyping (keras is highly modular, minimized, and extensible). Support for CNN and RNN or the combination of the two Supports arbitrary link schemes (including multiple input and multiple output training). Seamless CPU and GPU handoff)

Libsvm is a simple, easy-to-use, and efficient software for SVMclassification and regression. It solves C-SVM classification, nu-SVMclassification, one-class-SVM, epsilon-SVM regression, and nu-SVMregression. It also provides an automatic model selection tool forC-SVM classification. This document explains the use of libsvm.Libsvm is available at http://www.csie.ntu.edu.tw/~cjlin/libsvmPlease read the COPYRIGHT file before using libsvm.Table of Contents=================- Quick Start- Installation and Data Format- `svm-train" Usage- `svm-predict" Usage- `svm-scale" Usage- Tips on Practical Use- Examples- Precomputed Kernels - Library Usage- Java Version- Building Windows Binaries- Additional Tools: Sub-sampling, Parameter Selection, Format checking, etc.- MATLAB/OCTAVE Interface- Python Interface-

说明：  采用Python写的abaqus自动提取应力结果的命令(A command written by Python to automatically extract stress results from ABAQUS)

说明：  各种机器学习方法的源代码，包括决策树、随机森林、神经网络等(Source code of various machine learning methods, including decision tree, random forest, neural network, etc)

说明：  用于人脸识别中的5点特征模型，将人脸数据进行提取(Five-Point Feature Model for Face Recognition and Face Data Extraction)

说明：  how to apply morphological operators on images