资源列表
character-training-set
- 车牌识别，各省汉字训练集，全是手动筛选的，部分省市素材缺少所以缺乏样本-License plate recognition, Chinese character training set
Autoencoder_Code
- 深度学习的代码，用于手写数字体识别，包括了受限玻尔兹曼机(RBM)网络的实现-Code provided by Ruslan Salakhutdinov and Geoff Hinton
fireDetect-v1.0
- 火焰检测的程序，使用了图像的颜色特征和尺度不变特征SIFT以及加速鲁棒特征SURF对候选区域进行筛选，并结合火焰的运动特性来判断-Real-time fire and flame detection- version 1.0
OV7255_RAW8_RGB888_VGA
- FPGA实现，OV7255摄像头的采集，RAW格式转为RGB格式，用SDRAM存储，然后VGA显示-FPGA implementation, collection OV7255 camera, RAW format into RGB format, with SDRAM memory, and VGA display
CORDIC
- CORDIC的FPGA代码和modelsim仿真，亲测可用，精度较高-CORDIC FPGA code and modelsim simulation, pro-test available, high precision
Plate_Recognition_System
- 一种新的车牌识别方法，利用分级操作提高识别率-A Cascade Framework for a Real-Time Statistical Plate Recognition System
face-detection
- 实现人脸检测，能将人脸部分用红线框出，为人脸识别做了较好的基础。里面有检测照片。-Implement face detection, can face parts out of the box with a red line for face recognition do a good foundation.There are detected photos.
KPCA-ORL
- 随着人脸识别越来越受到重视，而人脸识别中特征降维又很重要，所以特征降维算法也很重要。因此PCA降维算法很重要-Dimensionality reduction for Face Recognition
syms-x-n[1]
- Fourier coefficients of a periodic function, without expression and function using only discrete values function in MATLAB
82692999pls
- 偏最小二乘（PLS），在保留输入变量的最大信息条件小，现在输入和输出组中建立模型，再用非线性迭代法提取类间特征-Partial Least Squares (PLS), in the small reservation conditions for maximum information input variables, input and output modeling group now and then between nonlinear iterative feature extract
siftDemoV4
- SIFT算法是近几年才提出的一种新型局部特征描述子。SIFT特征独特性好，信息量丰富，对尺度缩放，旋转，视角变化，遮挡，噪声和亮度变化等大部分干扰都具有很好的鲁棒性，它在在场景匹配，目标识别等领域已获得成功利用-SIFT algorithm is a new feature in recent years that it has made a partial descr iption of the child. SIFT features unique and good, rich amount
kda-1.0
- 基于KDA的人脸识别首先利用核方法将人脸图像数据集非线性映射到一个高维特征空间中，然后在高维特征空间中利用LDA进行线性特征提取-Face recognition based on first use of nuclear KDA method will face image data set nonlinear mapping to a high dimensional feature space, and then use LDA in high-dimensional feature sp