登录
首页 » Python » 卷积神经网络用于两幅遥感图像或者红外和可见光图像的融合 CNN-Fusion

卷积神经网络用于两幅遥感图像或者红外和可见光图像的融合 CNN-Fusion

于 2020-08-27 发布
0 212
下载积分: 1 下载次数: 9

代码说明:

说明:  卷积神经网络用于两幅遥感图像或者红外和可见光图像的融合(For fusion of two remote sensing images or infrared and visible images)

文件列表:

CNN-Fusion, 0 , 2020-04-27
CNN-Fusion\.idea, 0 , 2020-04-20
CNN-Fusion\.idea\CNN-Fusion-master.iml, 638 , 2020-03-28
CNN-Fusion\.idea\inspectionProfiles, 0 , 2020-05-06
CNN-Fusion\.idea\misc.xml, 294 , 2020-03-27
CNN-Fusion\.idea\modules.xml, 293 , 2020-03-27
CNN-Fusion\.idea\workspace.xml, 26874 , 2020-04-20
CNN-Fusion\__pycache__, 0 , 2020-03-28
CNN-Fusion\__pycache__\cifar_data_hls.cpython-36.pyc, 5853 , 2020-03-28
CNN-Fusion\__pycache__\fusion_model.cpython-36.pyc, 12026 , 2020-03-28
CNN-Fusion\cifar_data_hls.py, 6383 , 2020-03-28
CNN-Fusion\fusion image, 0 , 2020-05-06
CNN-Fusion\fusion image\fusion1.jpg, 45721 , 2020-04-19
CNN-Fusion\fusion image\fusion2.jpg, 16969 , 2020-04-19
CNN-Fusion\fusion.py, 955 , 2020-04-20
CNN-Fusion\fusion_model.py, 15723 , 2020-03-28
CNN-Fusion\image, 0 , 2020-05-06
CNN-Fusion\image\ms1.jpg, 33350 , 2019-04-25
CNN-Fusion\image\ms2.jpg, 12150 , 2019-04-25
CNN-Fusion\image\pan1.jpg, 39964 , 2019-04-25
CNN-Fusion\image\pan2.jpg, 15772 , 2019-04-25
CNN-Fusion\logs, 0 , 2020-04-20
CNN-Fusion\logs\fusion_model, 0 , 2020-04-20
CNN-Fusion\logs\fusion_model\events.out.tfevents.1587390923.DESKTOP-GAK6HHP, 888503 , 2020-04-20
CNN-Fusion\saves, 0 , 2020-03-27
CNN-Fusion\saves\fusion_model, 0 , 2020-03-27
CNN-Fusion\saves\fusion_model\checkpoint, 77 , 2019-04-25
CNN-Fusion\saves\fusion_model\model.ckpt.data-00000-of-00001, 7794476 , 2019-04-25
CNN-Fusion\saves\fusion_model\model.ckpt.index, 5604 , 2019-04-25
CNN-Fusion\saves\fusion_model\model.ckpt.meta, 450860 , 2019-04-25
CNN-Fusion\train.py, 948 , 2020-03-28
CNN-Fusion\venv, 0 , 2020-03-28
CNN-Fusion\venv\000.py, 44 , 2020-03-28
CNN-Fusion\venv\Include, 0 , 2020-05-06
CNN-Fusion\venv\Lib, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\easy-install.pth, 55 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\EGG-INFO, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\EGG-INFO\PKG-INFO, 2972 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\EGG-INFO\SOURCES.txt, 12502 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\EGG-INFO\dependency_links.txt, 1 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\EGG-INFO\entry_points.txt, 98 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\EGG-INFO\not-zip-safe, 2 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\EGG-INFO\requires.txt, 74 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\EGG-INFO\top_level.txt, 4 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\__init__.py, 24 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\__main__.py, 629 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\__init__.py, 8675 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\basecommand.py, 14014 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\baseparser.py, 8764 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\build_env.py, 2773 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\cache.py, 7023 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\cmdoptions.py, 16679 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\__init__.py, 2297 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\check.py, 1500 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\completion.py, 3018 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\configuration.py, 7343 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\download.py, 9092 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\freeze.py, 3320 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\hash.py, 1729 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\help.py, 1079 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\install.py, 20270 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\list.py, 11957 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\search.py, 4842 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\show.py, 6378 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\uninstall.py, 2786 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\commands\wheel.py, 6986 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\compat.py, 7912 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\configuration.py, 13330 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\download.py, 34257 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\exceptions.py, 8470 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\index.py, 41718 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\locations.py, 6504 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\models, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\models\__init__.py, 85 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\models\index.py, 433 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\operations, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\operations\__init__.py, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\operations\check.py, 3776 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\operations\freeze.py, 10277 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\operations\prepare.py, 15496 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\pep425tags.py, 11115 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\req, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\req\__init__.py, 2152 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\req\req_file.py, 12248 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\req\req_install.py, 43930 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\req\req_set.py, 7268 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\req\req_uninstall.py, 17002 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\resolve.py, 13939 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\status_codes.py, 164 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\utils, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\utils\__init__.py, 0 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\utils\appdirs.py, 9372 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\utils\deprecation.py, 2374 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\utils\encoding.py, 1058 , 2020-03-27
CNN-Fusion\venv\Lib\site-packages\pip-10.0.1-py3.6.egg\pip\_internal\utils\filesystem.py, 937 , 2020-03-27

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

  • twain_vb
    twain_vb源码,图像设备与计算机软件接口程序(twain_vb)
    2010-05-13 13:43:52下载
    积分:1
  • MPD++
    NASA开源的匹配追踪分解算法,用于信号分解以及特征提取。(Matching Pursuit Decomposition is a powerful and effective iterative algorithm for signal decomposition and feature extraction. Matching Pursuit Decomposition decomposes any signal into linear combinations of its dictionary elements or atoms.)
    2019-03-01 15:08:05下载
    积分:1
  • 基于matlab像处理系统
    说明:  图像处理MATLABGUI界面,实现对输入图像的超分辨率重建(image processing interface; boundary; limiting surface realize; achieve; bring about; come true rebuild; reconstruct; reestablish; rehabilitate)
    2021-02-19 16:09:45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
  • siftDemoV4
    lowe论文的sift算法的MATLAB源代码(MATLAB source code of sift algorithm for lowe paper)
    2019-06-12 10:11:30下载
    积分:1
  • segmentation
    基于K均值算法和互信息熵差的算法,可以有效地确定分类数,从而该算法对医学图像进行自动优化分割。(K means algorithm based on entropy and mutual information algorithms, can effectively determine the classification number, so that the algorithm for automatic optimization of medical image segmentation.)
    2021-03-24 16:49:15下载
    积分:1
  • English-sentence-sim
    英文文本的相似度计算,分别从词形、词序、词义等方面进行权重计算,得到相似度结果(English text similarity calculation were re-calculated from the word form, word order, meaning, etc. right, the similarity results)
    2014-01-14 17:26:29下载
    积分:1
  • PML-v1.0
    说明:  Projection Metric Learning on Grassmann Manifold with Application to Video based Face Recognition
    2020-11-17 13:59:40下载
    积分:1
  • cdf
    基于DMRS和CP的频偏估计算法仿真,算法的CDF曲线(Simulation of frequency offset estimation algorithm based on DMRS and CP)
    2017-11-22 19:19:01下载
    积分:1
  • 第三章像灰度直方变换
    在数字图像处理中,灰度直方图是最简单且最有用的工具,可以说,对图像的分析与观察直到形成一个有效的处理方法,都离不开直方图。(in digital image processing, the histogram is the simplest and most useful tool, it can be said that the right image analysis and observation until the formation of an effective treatment method has been based on histogram.)
    2005-06-06 19:38:58下载
    积分:1
  • 696518资源总数
  • 104347会员总数
  • 12今日下载