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Image Processing Using Deep Learning

Extend deep learning workflows with image processing applications

Apply deep learning to image processing applications by using Deep Learning Toolbox™ together with Image Processing Toolbox™.

Functions

augmentedImageDatastoreTransform batches to augment image data
randomPatchExtractionDatastoreDatastore for extracting random 2-D or 3-D random patches from images or pixel label images
blockedImageDatastoreDatastore for use with blocks from blockedImage objects

Topics

Preprocess Data for Domain-Specific Deep Learning Applications

Perform deterministic or randomized data processing for domains such as image processing, object detection, semantic segmentation, signal and audio processing, and text analytics.

Augment Images for Deep Learning Workflows Using Image Processing Toolbox

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

Preprocess Images for Deep Learning

Learn how to resize images for training, prediction, and classification, and how to preprocess images using data augmentation, transformations, and specialized datastores.

Preprocess Volumes for Deep Learning

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

Preprocess Multiresolution Images for Training Classification Network (Image Processing Toolbox)

This example shows how to prepare datastores that read and preprocess multiresolution whole slide images (WSIs) that might not fit in memory.

Get Started with GANs for Image-to-Image Translation (Image Processing Toolbox)

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

Featured Examples