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人脸识别系统设计—毕业设计
- 本课题的主要内容是图像预处理,它主要从摄像头中获取人脸图像然后进行处理,以便提高定位和识别的准确率.该模块主要包含光线补偿、图像灰度化、高斯平滑、均衡直方图、图像对比度增强，图像预处理模块在整个系统中起着极其关键的作用，图像处理的好坏直接影响着后面的定位和识别工作,内有源代码和全部论文资料-this issue is the major content of image preprocessing, mainly from the camera to obtain images Face the
Xerdoc XDMF
- 一个比较好用的中文分词模块,是车东等人开发的,比较有名,java语言实现-a better quality of the Chinese word module, East cars were developed, more famous, java language!
jswarm-pso_1_1
- JSwarn 是微粒群优化(PSO) 程序包被写在Java. 设计要求极小的工作成绩使用(在配件箱外面) 虽然同样高模件。 -JSwarn Particle Swarm Optimization (PSO) package written in Java. The minimum design requirements of the Public results for the use (in the outside box accessories) Although the same hig
ga_pic
- 基于遗传算法的图案生成程序，其中有遗传算法的基本模块。-based on genetic algorithm design generation procedures, which are the basic genetic algorithm module.
112611712642
- 特别是在题库管理模块中对自动组卷功能常用的算法（包括随机选取法、回溯试探法和遗传算法）进行了比较。对于较流行的验证码技术也给出了具体实现。-particularly in the examination management module to automatically making up the algorithm commonly used functions (including random selection method, Retrospective testing and gen
Statistics-ROC-0.04.tar
- A Perl module implementing receiver-operator-characteristic (ROC) curves with nonparametric confidence bounds
sjwl
- 神经网络（模式识别模块）软件开发包!!!可以识别任何事物，适用于图像识别、语音识别、自动控制等诸多领域，具有简单、易学、开发周期短、识别率高等特点。-neural network (pattern recognition module) software development kit! ! ! Nothing can be identified and applied to image recognition, voice recognition, automatic control and
BP神经网络源程序
- 基于C开发的三个隐层神经网络，输出权值、阈值文件，训练样本文件，提供如下函数：1）初始化权、阈值子程序；2）第m个学习样本输入子程序；3）第m个样本教师信号子程序；4）隐层各单元输入、输出值子程序；5）输出层各单元输入、输出值子程序；6）输出层至隐层的一般化误差子程序；7）隐层至输入层的一般化误差子程序；8）输出层至第三隐层的权值调整、输出层阈值调整计算子程序；9）第三隐层至第二隐层的权值调整、第三隐层阈值调整计算子程序；10）第二隐层至第一隐层的权值调整、第二隐层阈值调整计算子程序；11）第一
k-means
- 基于K-means聚类算法的社团发现方法 先定义了网络中节点关联度,并构建了节点关联度矩阵, 在此基础上给出了一种基于 K-means聚类算法的复杂网络社团发现方法。 以最小关联度原则选取新的聚类中心, 以最大关联度原则进行模式归类,直到所有的节点都划分完为止, 最后根据模块度来确定理想的社团数-K-means clustering algorithm based on the association discovery To define a network node cor
ce_su001
- MC9S12DG128 飞思卡尔比赛 测速模块-Freescale MC9S12DG128 gun game module
SA
- 模拟退火基本模块，其中在尺度变换部分应用到了类似模拟退火算法部分，所有变量均使用汉语拼音很好懂-Simulated Annealing basic module, in which part of the scale transformation is applied to a similar part of simulated annealing algorithm, all variables are very good to understand the use of Hanyu Piny
ycsf
- 通过两点之间的距离来实现多点之间的相互定位，利用遗传算法实现，可用于Zigbee模块的室内定位。-Through the distance between two points to achieve multi-point between the positioning, the use of genetic algorithm, can be used for indoor positioning Zigbee module.
Sixteen
- According to trilearn_base_sources-3.3 (generally known as UVA bottom) to amend the code of RoboCup teams, for certain modules in detail the Notes (such as BasicPlayer, WorldMode module), and carried out some basic moves to add a model (an increase o
Radian
- According to trilearn_base_sources-3.3 (generally known as UVA bottom) to amend the code of RoboCup teams, for certain modules in detail the Notes (such as BasicPlayer, WorldMode module), and carried out some basic moves to add a model (an increase o
2in1
- 使用全互联迭代神经网络构造的输出自减模块-Make use of the Internet iterative neural network constructed by the output from the module
simultaneous
- 利用遗传算法对两个神经网络模块共同进化的例子，此方法优于对两个模块分别进化-Using the genetic algorithm neural network module of the two examples of co-evolution, this method is superior to the evolution of the two modules were
BPC
- 中国BPC码模块技术协议(二次开发技术协议).-China BPC yards Module Technology Agreement (secondary development technology agreements).
SnOW
- This package provides a Maximum Entropy Modeling toolkit written in C++ with Python binding. It includes: Conditional Maximum Entropy Model L-BFGS Parameter Estimation GIS Parameter Estimation Gaussian Prior Smoothing C++ API
RoboCup
- 文章从功能分析、结构设计、软件实现三个层面，逐步求精的设计实现混合的Agent体系结构，规划各模块的功能和接口，并解决Agent与Server的同步问题。 介绍底层通信器、感知器、执行器的实现。 第五章使用类图设计世界模型的结构，设计更新算法融入各种感知信息和动作 预测，依据基本信息推导出一些球场状况判断函数为高层决策所用。 介绍了建立四层动作模型，采用解析计算法实现多种个人技术动作，如跑位、 截球、传球、带球、射门、守门等。-Articles from functional
weka
- 很详细地介绍了weka的数据挖掘功能，尤其是分类模块很完善。-Very detailed descr iption of the weka data mining function, especially the classification module is perfect.