-
Isomap
truncated DCT. good for video compression.
- 2012-06-07 07:05:07下载
- 积分：1
-
史上最快人脸检测系统（超越OpenCV）
史上最快人脸检测系统（超越OpenCV）
- 2019-03-19下载
- 积分：1
-
dashline
一个简单的虚线类，绘制各种虚线的C++类库，请看效果截图，可绘制出各种彩色的虚线效果。画横向或竖向虚线，以及对角线的虚线框效果，都是可以的，带有一个演示程序。(A simple dashed class, draw various dashed C++ library, see the effects shots, you can draw a variety of color dotted effect. Draw horizontal or vertical dashed line, as well as the effect of diagonal dashed box, are possible with a demo program.)
- 2021-05-14 14:30:02下载
- 积分：1
-
multiquadric
输入控制点对，即可得到畸变校正系数。
此例中使用最近临插值。如要得到更好效果，可换用双线性或3次插值。(Input control point right, you get distortion correction factor. In this case, using the most recent clinical interpolation. To get better results, can be used for bilinear interpolation or 3 times.)
- 2008-02-23 22:32:45下载
- 积分：1
-
sar_rd
说明： 使用matlab平台进行斜视角为0度的九点目标RD算法仿真(Simulation of nine point target Rd algorithm with 0 degree squint angle using MATLAB platform)
- 2019-11-12 15:57:02下载
- 积分：1
-
FCLS
全约束最小2乘法，用于遥感图像的混合象元分解(2 multiply constrained minimum-wide, the mixed-use remote sensing image pixel decomposition)
- 2021-02-24 09:49:39下载
- 积分：1
-
Nonsubsampled-Contourlet-Transform
非下采样contourlet相关去噪，论文程序，包括非下采样contourlet变换工具箱，已通过仿真(Related denoising nonsubsampled contourlet paper program, including non-sampling contourlet transform toolbox has been through the simulation)
- 2012-08-10 21:30:38下载
- 积分：1
-
DoGfilters
说明： DOG高斯差分实现物体识别中的特征提取,对不同尺度空间的图像进行差分，从而获得描述物体的特征值(difference of gaussian to achieve the feature point exaction of object recognition)
- 2010-03-30 20:08:39下载
- 积分：1
-
bayesthresholding
基于小波的去噪算法，采用BAYES原理选取阈值，源代码，参考文献：Adaptive Wavelet Thresholding for Image Denoising
and Compression(Wavelet-based denoising algorithm using the principle to select threshold BAYES, source code references: Adaptive Wavelet Thresholding for Image Denoisingand Compression)
- 2020-09-22 10:47:51下载
- 积分：1
-
ssd.pytorch
说明： SSD: Single Shot MultiBox Object Detector, in PyTorch
A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang, and Alexander C. Berg. The official and original Caffe code can be found here.
Table of Contents
Installation
Datasets
Train
Evaluate
Performance
Demos
Future Work
Reference
- 2020-06-25 07:00:02下载
- 积分：1
