资源列表
dbscan-clustering
- Implementation of DBSCAN Clustering in MATLAB
rspcafnni
- 模糊神经网络图像识别, 基于人脸PCA算法的人脸检测识别，LDA特征提取，模糊神经隶属度算法-Fuzzy Neural Network Image Recognition
hongwiashipi
- 基于人工神经网络的红外目标识别与跟踪，运行环境为VISUAL STUDIO OPENCV3环境-Based on artificial neural network infrared target recognition and tracking, the operating environment for the VISUAL STUDIO OPENCV3 environment
CPPADA
- C+++视频cvncvb监控系统,根据支持向量机的特征提取对视频中的物体进行检测识别-C++ video cvbcvb monitoring system, according to the support vector machine to extract the characteristics of the object in the video detection and identification
Masaike_Detection
- 视频在解码过程中，有时候需要检测是否含有马赛克帧，及时去除以提高视频质量。这里利用多线程，实现了视频解码过程中马赛克实时检测。-Video in the decoding process, and sometimes need to detect whether it contains mosaic frame, timely removal to improve the video quality. Here the use of multi-threaded, to achieve the
smokedetection
- 用VS2010和OPENCV编写的关于视频烟雾检测的程序，运行效果很好-With VS2010 and OPENCV prepared on the video smoke detection procedures, running very well
class
- 利用支持向量机对男女的身高体重建立数学模型，然后来预测性别-Use the support vector machine to establish a mathematical model for the height and weight of men and women, and then to predict gender
ensemble
- 对分类错误的样本所对应权重进行累加得到加权误分类率, 这里我们是基于权重向量而不是其他的错误计算指标来评价分类器的-The weighting of the samples with the wrong classification is weighted by the weighted error rate, where we uate the classifier based on the weight vector rather than the other erroneous met
renkou
- 对人口数量进行数学建模，利用神经网络算法对它的分布进行预测-The mathematical modeling of the population quantity is carried out, and the distribution of the population is predicted by the neural network algorithm
Bee-colony-algorithm-source-code
- 基本的(Artificial bee colony algorithm ABC)人工蜂群算法源代码，本人亲自测试并通过的，使用C语言编写。-The basic (Artificial bee colony algorithm ABC) artificial bee colony algorithm source code, the use of C language.
plot_classifier_comparison
- 调用机器学习库sk-learn中的svm，KNeighborsC，GaussianProcess算法进行分类任务，并且比较这几种算法在三种场景下的性能-Using machine learning libraries sk- learn the SVM, KNeighborsC, GaussianProcess algorithm classification task, and comparing the several kinds of algorithm in the performanc
fdICA
- 本代码主要提供了在频域使用fastica进行盲源分离，并且解决了频域的排列和增益两个歧义性问题。-This code mainly provides the use of fastica in the frequency domain for blind source separation, and solves the frequency domain arrangement and gain of two ambiguity problems.