▍1. deeplab V3和unet
说明: 利用全卷积神经网络,实现图像的语义分割,基于tensorflow的keras可以直接运行(Using the full convolutional neural network to achieve semantic segmentation of images, keras based on tensorflow can be run directly)
说明: 利用全卷积神经网络,实现图像的语义分割,基于tensorflow的keras可以直接运行(Using the full convolutional neural network to achieve semantic segmentation of images, keras based on tensorflow can be run directly)
HOG LBP 在python matlab C++环境下的实现(Implementation of HOG LBP in Python matlab C++ environment)
说明: HOG LBP 在python matlab C++环境下的实现(Implementation of HOG LBP in Python matlab C++ environment)
使用python语言实现多张图像的拼接,并且处理拼接之后的裂缝和黑边。(Use python language to achieve splicing of multiple images, and deal with cracks and black edges after splicing.)
说明: 使用python语言实现多张图像的拼接,并且处理拼接之后的裂缝和黑边。(Use python language to achieve splicing of multiple images, and deal with cracks and black edges after splicing.)
使用tensorflow框架搭建神经网络,从单目图像中估计深度值(Using tensorflow framework to build a neural network to estimate depth from monocular images)
说明: 使用tensorflow框架搭建神经网络,从单目图像中估计深度值(Using tensorflow framework to build a neural network to estimate depth from monocular images)
说明: 利用python写的简单降噪程序(根据一个点A的RGB值,与周围的8个点的RBG值比较,设定一个值N(0
这个程序可以用于两个图像的拼接,通过寻找特征点完成拼接(This program can be used to stitch two images and complete the stitching by finding feature points.)
说明: 这个程序可以用于两个图像的拼接,通过寻找特征点完成拼接(This program can be used to stitch two images and complete the stitching by finding feature points.)
利用卷积神经网络进行特征提取,并将卷积特征可视化(Feature extraction using convolutional neural networks and visualization of convolution features)
说明: 利用卷积神经网络进行特征提取,并将卷积特征可视化(Feature extraction using convolutional neural networks and visualization of convolution features)
Python 分水岭算法 用于图像分割等图像处理(Python watershed algorithm)
说明: Python 分水岭算法 用于图像分割等图像处理(Python watershed algorithm)
利用传统的SVM-HOG算法,进行行人检测(HOG-SVM algorithm for pedestrian detection)
训练了一个CNN模型用于土地资源分类,适用于遥感图像(A CNN model is trained for land use classification and is suitable for remote sensing images.)