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使用深度学习进行图像处理

使用卷积神经网络执行图像处理任务,例如去除图像噪声和基于低分辨率图像创建高分辨率图像(需要 Deep Learning Toolbox™)

深度学习使用神经网络直接从数据中学习有用的特征表示。例如,您可以使用预训练神经网络来识别和去除图像中的噪声等项。

函数

全部展开

augmentedImageDatastoreTransform batches to augment image data
blockedImageDatastoreDatastore for use with blocks from blockedImage objects
denoisingImageDatastoreDenoising image datastore
imageDatastore图像数据的数据存储
randomPatchExtractionDatastoreDatastore for extracting random 2-D or 3-D random patches from images or pixel label images
transform变换数据存储
combine合并来自多个数据存储的数据
jitterColorHSVRandomly alter color of pixels
randomWindow2dRandomly select rectangular region in image
randomCropWindow3dCreate randomized cuboidal cropping window
centerCropWindow2dCreate rectangular center cropping window
centerCropWindow3dCreate cuboidal center cropping window
RectangleSpatial extents of 2-D rectangular region
CuboidSpatial extents of 3-D cuboidal region
randomAffine2dCreate randomized 2-D affine transformation
randomAffine3dCreate randomized 3-D affine transformation
affineOutputViewCreate output view for warping images
imeraseRemove image pixels within rectangular region of interest
resize2dLayer2-D resize layer
resize3dLayer3-D resize layer
dlresizeResize spatial dimensions of dlarray object
DepthToSpace2DLayerDepth to space layer
SpaceToDepthLayerSpace to depth layer
depthToSpaceRearrange dlarray data from depth dimension into spatial blocks
spaceToDepthRearrange spatial blocks of dlarray data along depth dimension
encoderDecoderNetworkCreate encoder-decoder network
blockedNetworkCreate network with repeating block structure
pretrainedEncoderNetworkCreate encoder network from pretrained network
cycleGANGeneratorCreate CycleGAN generator network for image-to-image translation
patchGANDiscriminatorCreate PatchGAN discriminator network
pix2pixHDGlobalGeneratorCreate pix2pixHD global generator network
addPix2PixHDLocalEnhancerAdd local enhancer network to pix2pixHD generator network
unitGeneratorCreate unsupervised image-to-image translation (UNIT) generator network
unitPredictPerform inference using unsupervised image-to-image translation (UNIT) network
denoiseImageDenoise image using deep neural network
denoisingNetworkGet image denoising network
dnCNNLayersGet denoising convolutional neural network layers

主题

预处理图像以进行深度学习

Datastores for Deep Learning (Deep Learning Toolbox)

Learn how to use datastores in deep learning applications.

Augment Images for Deep Learning Workflows Using Image Processing Toolbox (Deep Learning Toolbox)

This example shows how MATLAB® and Image Processing Toolbox™ can perform common kinds of image augmentation as part of deep learning workflows.

预处理图像以进行深度学习 (Deep Learning Toolbox)

了解如何调整图像大小以进行训练、预测和分类,以及如何使用数据增强、变换和专用数据存储对图像进行预处理。

Preprocess Volumes for Deep Learning (Deep Learning Toolbox)

Read and preprocess volumetric image and label data for 3-D deep learning.

创建用于图像处理应用的神经网络

Create Modular Neural Networks

You can create and customize deep learning networks that follow a modular pattern with repeating groups of layers, such as U-Net and cycleGAN.

Get Started with GANs for Image-to-Image Translation

GAN networks can transfer the styles and characteristics from one set of images to the scene content of other images.

使用深度学习对图像去噪

Train and Apply Denoising Neural Networks

Use a pretrained neural network to remove Gaussian noise from a grayscale image, or train your own network using predefined layers.

使用预训练的神经网络去除彩色图像中的噪声

此示例说明如何通过独立地对每个颜色通道使用预训练去噪神经网络来从 RGB 图像中去除高斯噪声。

为图像到图像的回归准备数据存储 (Deep Learning Toolbox)

此示例说明如何准备数据存储,以便使用 ImageDatastoretransformcombine 函数来训练图像到图像的回归网络。

MATLAB 中进行深度学习

在 MATLAB 中进行深度学习 (Deep Learning Toolbox)

通过使用卷积神经网络进行分类和回归来探索 MATLAB® 的深度学习能力,包括预训练网络和迁移学习,以及在 GPU、CPU、群集和云上进行训练。

预训练的深度神经网络 (Deep Learning Toolbox)

了解如何下载和使用预训练的卷积神经网络进行分类、迁移学习和特征提取。

Semantic Segmentation Using Deep Learning (Computer Vision Toolbox)

This example shows how to train a semantic segmentation network using deep learning.

深度学习层列表 (Deep Learning Toolbox)

探索 MATLAB 中的所有深度学习层。

特色示例