登录
首页 » matlab » DENTIST-master

DENTIST-master

于 2020-10-19 发布
0 204
下载积分: 1 下载次数: 2
我要下载

代码说明：

说明：  红外小目标检测算法RIPI，基于红外块图像，张量加权，PCA(infrared target detection algorithm RIPI)

文件列表：

DENTIST-master\algorithms\detection\NIPPS\demo_generate_nipps_data.m, 1244 , 2020-06-17
DENTIST-master\algorithms\detection\NIPPS\nipps.m, 2649 , 2018-08-01
DENTIST-master\algorithms\detection\NIPPS\README.md, 685 , 2018-08-01
DENTIST-master\algorithms\detection\RIPT\1.avi, 1054838 , 2018-08-29
DENTIST-master\algorithms\detection\RIPT\2.avi, 917728 , 2018-08-29
DENTIST-master\algorithms\detection\RIPT\3.avi, 205056 , 2018-10-02
DENTIST-master\algorithms\detection\RIPT\demo_generate_RIPT_data.m, 1961 , 2019-07-09
DENTIST-master\algorithms\detection\RIPT\mat2ten.m, 645 , 2018-08-01
DENTIST-master\algorithms\detection\RIPT\prox_non_neg_l1.m, 73 , 2018-08-01
DENTIST-master\algorithms\detection\RIPT\res_patch_ten_mean.m, 1139 , 2018-08-01
DENTIST-master\algorithms\detection\RIPT\ript.m, 2285 , 2018-08-01
DENTIST-master\algorithms\detection\RIPT\structure_tensor_lambda.m, 1181 , 2019-07-10
DENTIST-master\algorithms\detection\RIPT\ten2mat.m, 528 , 2018-08-01
DENTIST-master\dataset\README.md, 489 , 2018-08-01
DENTIST-master\dataset\Set_11\1.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\10.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\11.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\12.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\13.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\14.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\15.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\16.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\17.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\18.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\19.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\2.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\20.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\21.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\22.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\23.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\24.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\25.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\26.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\27.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\28.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\29.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\3.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\30.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\4.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\5.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\6.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\7.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\8.bmp, 153654 , 2018-08-01
DENTIST-master\dataset\Set_11\9.bmp, 153654 , 2018-08-01
DENTIST-master\funcSCR1.m, 1484 , 2018-12-24
DENTIST-master\libs\PROPACK\Afunc.m, 202 , 2018-08-01
DENTIST-master\libs\PROPACK\AtAfunc.m, 224 , 2018-08-01
DENTIST-master\libs\PROPACK\Atransfunc.m, 232 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr.m, 987 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr.mexglx, 74546 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr.mexsg, 25208 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr.mexsg64, 26109 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr.mexsol, 95852 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr.mexw32, 55808 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr_mex.c, 2102 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr_mex.exp, 665 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr_mex.lib, 1836 , 2018-08-01
DENTIST-master\libs\PROPACK\bdsqr_mex.mexw64.manifest, 381 , 2018-08-01
DENTIST-master\libs\PROPACK\Cfunc.m, 293 , 2018-08-01
DENTIST-master\libs\PROPACK\compute_int.m, 1504 , 2018-08-01
DENTIST-master\libs\PROPACK\dbdqr.f, 445 , 2018-08-01
DENTIST-master\libs\PROPACK\helio.mat, 256353 , 2018-08-01
DENTIST-master\libs\PROPACK\lanbpro.doc, 3544 , 2018-08-01
DENTIST-master\libs\PROPACK\lanbpro.m, 19514 , 2018-08-01
DENTIST-master\libs\PROPACK\lanbpro.txt, 3544 , 2018-08-01
DENTIST-master\libs\PROPACK\laneig.doc, 2522 , 2018-08-01
DENTIST-master\libs\PROPACK\laneig.m, 9695 , 2018-08-01
DENTIST-master\libs\PROPACK\laneig.txt, 2522 , 2018-08-01
DENTIST-master\libs\PROPACK\lanpro.doc, 3336 , 2018-08-01
DENTIST-master\libs\PROPACK\lanpro.m, 14762 , 2018-08-01
DENTIST-master\libs\PROPACK\lanpro.txt, 3336 , 2018-08-01
DENTIST-master\libs\PROPACK\lansvd.doc, 2386 , 2018-08-01
DENTIST-master\libs\PROPACK\lansvd.m, 9307 , 2018-08-01
DENTIST-master\libs\PROPACK\lansvd.txt, 2386 , 2018-08-01
DENTIST-master\libs\PROPACK\mminfo.m, 3238 , 2018-08-01
DENTIST-master\libs\PROPACK\mmread.m, 7224 , 2018-08-01
DENTIST-master\libs\PROPACK\mmwrite.m, 6574 , 2018-08-01
DENTIST-master\libs\PROPACK\pythag.m, 618 , 2018-08-01
DENTIST-master\libs\PROPACK\refinebounds.m, 939 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth.f, 3580 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth.m, 2663 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth.mexglx, 9640 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth.mexsg, 25428 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth.mexsg64, 26694 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth.mexsol, 86872 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth_mex.c, 2828 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth_mex.exp, 666 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth_mex.lib, 1846 , 2018-08-01
DENTIST-master\libs\PROPACK\reorth_mex.mexw64.manifest, 381 , 2018-08-01
DENTIST-master\libs\PROPACK\test.m, 9510 , 2018-08-01
DENTIST-master\libs\PROPACK\testtqlb.m, 1611 , 2018-08-01
DENTIST-master\libs\PROPACK\tqlb.f, 5442 , 2018-08-01
DENTIST-master\libs\PROPACK\tqlb.m, 852 , 2018-08-01
DENTIST-master\libs\PROPACK\tqlb.mexglx, 9515 , 2018-08-01
DENTIST-master\libs\PROPACK\tqlb.mexsg, 25564 , 2018-08-01
DENTIST-master\libs\PROPACK\tqlb.mexsg64, 27536 , 2018-08-01
DENTIST-master\libs\PROPACK\tqlb.mexsol, 9676 , 2018-08-01
DENTIST-master\libs\PROPACK\tqlb_mex.c, 1301 , 2018-08-01
DENTIST-master\libs\PROPACK\tqlb_mex.exp, 662 , 2018-08-01
DENTIST-master\libs\PROPACK\tqlb_mex.lib, 1744 , 2018-08-01

下载说明：请别用迅雷下载，失败请重下，重下不扣分！

发表评论

0 个回复

  • 7.3.1
    一维数据的Kalman滤波处理，线性卡尔曼滤波的Simulink仿真(Kalman filter processing for one-dimensional data, Simulink simulation for linear Kalman filtering)
    2018-07-19 09:38:49下载
    积分：1
  • keshe
    条形码生成工具：利用此工具可自动生成条形码(Bar code generation tool)
    2012-12-26 12:45:15下载
    积分：1
  • 3DGame
    introduce 3d with dx9.0 绝好的3d书籍加源码(introduce 3d with dx9.0 excellent books on Canadian source 3d)
    2010-02-27 12:57:55下载
    积分：1
  • 3D_PSTD
    说明：  使用PSTD计算方法实现的3维时间反转镜像技术算法，可用于声学及电磁学成像(A Time Reversal Mirror Algrithm devopled by the 3 dimensial PSTD numerical method, it can be used in acousic and electromagnitic imaging field)
    2009-08-25 15:39:59下载
    积分：1
  • OpenCV-Computer-Vision-With-Python
    本书叙述如何使用Python中的OpenCV库实现视频捕捉、图像处理、目标检测等功能。(This book will show you how to use OpenCV s Python bindings to capture video, manipulate images, and track objects with either a normal webcam or a specialized depth sensor, such as the Microsoft Kinect.)
    2021-04-24 16:48:48下载
    积分：1
  • CN_edgedetect
    本程序为二值图像的处理。通过一种称为CNED(connectivity number based edge detection)的方法对二值图像进行边缘提取。结果表明这种方法比candy sober 等算子更加精确，效果更好。(This procedure for binary image processing. Through a known CNED (connectivity number based edge detection) method for binary image edge extraction. The results show that this method, such as candy sober than the operator more precise, better.)
    2007-04-22 13:23:27下载
    积分：1
  • 图形学
    图形学DDA算法(graphics algorithm)
    2004-11-19 08:39:02下载
    积分：1
  • mfile
    说明：  批量提取遥感影像数据，以如何在一个文件批量读取geotif数据为例(Batch extraction of remote sensing image data)
    2021-01-18 21:00:52下载
    积分：1
  • PCA
    主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)
    2021-01-28 21:48:40下载
    积分：1
  • med
    matlab中值平滑处理,主要是用5点平滑和3点平滑实现(matlab median smoothing was used in 5-point smoothing and 3 points to achieve smooth)
    2009-11-03 11:38:00下载
    积分：1
  • 696518资源总数
  • 105885会员总数
  • 31今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2025 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！