-
display_features
MSER算法的一部分，不知道该怎么运行，请大家帮忙(is part of the MSER algorithm )
- 2009-11-30 09:35:11下载
- 积分：1
-
CameraCalibration
说明： 完整的相机标定程序，基于张正友标定板，用于相机的内参外参标定。(Complete camera calibration procedure, based on Zhang Zhengyou calibration board, is used for camera internal and external parameters calibration.)
- 2019-07-01 10:44:10下载
- 积分：1
-
prims_matlab
prims算法遗传算法 PID 控制，多变量解耦 PID 控制，几种先进的PID 控制，灰色 PID 控制，伺服系统 PID 控制，PID 实时控制，每种方法都通过 MATLAB 仿真程序进行了说明。本书各部分内容既相互联系又相互独立，读者可根据自己需要选择学习。本书适用于从事生产过程自动化、计算机应用、机械电子和电气自动化领域工作的工程技术人员阅读，也可作为大专院校工业自动化、自动控制、机械电子、自动化仪表、计算机应用等专业的教学参考(prims genetic algorithms described in MATLAB tutorial)
- 2012-04-29 19:50:58下载
- 积分：1
-
generation
in this file is distributed system in two case
- 2013-09-20 11:59:41下载
- 积分：1
-
bayesleastrisk
基于最小风险的贝叶斯分类器，用于数字分类识别(Bayesian minimum risk classification for digital classification)
- 2013-10-25 17:35:13下载
- 积分：1
-
code
基于MATLAB环境下的人脸识别代码，简单易行，值得下载(Environment based on MATLAB code for face recognition, simple and easy, it is worth downloading)
- 2009-04-23 09:26:47下载
- 积分：1
-
EEG-preprocessing
这是关于脑电信号预处理的程序，希望对大家有帮助(This is about the brain electrical signal preprocessing procedure, I hope it can help you)
- 2020-07-01 07:20:02下载
- 积分：1
-
danbianpu3
FFT傅里叶变换频谱单边谱分析的matlab实现，已经过验证(failed to translate)
- 2013-05-08 20:11:51下载
- 积分：1
-
displayRelevantVisualWords
Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene.[2][3] The concept of optical flow was first studied in the 1940s and ultimately published by American psychologist James J. Gibson[4] as part of his theory of affordance. Optical flow techniques such as motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement utilize this motion of the objects surfaces and edges.[5][6]
- 2012-03-31 23:44:49下载
- 积分：1
-
JPEG_BaseLine_Encoder
The JPEG compression scheme is divided into the following stages:
1. Transform the image into an optimal color space.
2. Adjust Aspect Ratio 16:9
3. Digitization Scheme 4:2:0.
4. Apply a Discrete Cosine Transform (DCT) to blocks of pixels, thus removing redundant image data.
5. Quantize each block of DCT coefficients using weighting functions optimized for the human eye.
6. Encode the resulting coefficients (image data) using a Huffman variable word-length algorithm to remove redundancies in the coefficients.
7. Byte Stuffing.
8. Header JFIF
9. JPG Data Store
- 2013-05-04 23:30:46下载
- 积分：1
