资源列表
Mechanical arm
- 关于二维平面的液压机械臂的工作范围问题及两点最短路径规划问题(On the working range problem of two-dimensional planar hydraulic manipulators and the two-point shortest path planning problem)
detection.py
- Python+OpenCV实现的行人检测(Pedestrian Detection of Python + OpenCV Implementation)
noise genre
- 用matlab产生高斯,椒盐,泊松噪声图像的完整代码(poisson, gossip,noise,salt&pepper)
pcaeig
- 实现降维,提取特征,本程序是为了实现特定图片的分类,使用pca降维,然后提取出特征,那就可以使用分类器分类(Realization of dimensionality reduction and feature extraction)
图像拉伸
- 遥感图像处理,用直方均衡化方法、2%线性拉伸方法拉伸图像,亮度值分布均衡(Drawing images by histogram)
fenlei
- 利用hog提取特征输入到svm分类器中,适用于新手(Using hog extraction feature input to svm classifier, suitable for novices)
tuxiangchuli
- 对二维码图像进行灰度化、中值滤波、二值化、边缘检测、霍夫变换等预处理(The two-dimensional code image is grayscale, median filter, two valued, edge detection, Hough transform and other pre-processing.)
image
- 图像分割,识别目标,用于在药物领域的识别,效果很好,可以进行简单的测试(image segmention it use in medcion and the result is very good you can do simple test and use in some)
随机森林代码
- 基于GEE平台,landsat影像的随机森立法土地覆盖分类(Land cover classification based on the random son legislation based on the GEE platform.)
Untitled2
- BP神经网络基本原理概述:这种网络模型利用误差反向传播训练算法模型,能够很好地解决多层网络中隐含层神经元连接权值系数的学习问题,它的特点是信号前向传播、误差反向传播,简称BP(Back Propagation)神经网络。BP学习算法的基本原理是梯度最快下降法,即通过调整权值使网络总误差最小,在信号前向传播阶段,输入信号经输入层处理再经隐含层处理最后传向输出层处理;在误差反向传播阶段,将输出层输出的信号值与期望输出信号值比较得到误差,若误差较大则把误差信号传回隐含层直至输入层,在各层神经元中使用
26个字母识别 用matlab实现的
- 用matlab实现的26个字母识别。基于BP算法的字母识别其容错性和识别率相对较高,在有噪声的情况下训练其识别出错率也相应增加,许进一步改进。(26 letter recognition implemented with MATLAB.The letter recognition based on BP algorithm has a relatively high fault tolerance and recognition rate, and the error rate of recog
matlab中文字符的识别代码
- 基于BP人工神经网络的数字字符识别及MATLAB实现。(Digital character recognition and MATLAB implementation based on BP artificial neural network.)