Procesamiento de imágenes mediante deep learning
Realice tareas de procesamiento de imágenes, como eliminar el ruido de la imagen y realice una traducción entre imágenes, mediante técnicas de deep learning que usan redes neuronales profundas (requiere Deep Learning Toolbox™)
Las técnicas de deep learning usan redes neuronales para aprender representaciones útiles de ciertas características directamente a partir de los datos. Por ejemplo, se puede usar una red neuronal previamente entrenada para identificar y eliminar ciertos artefactos de una imagen, como el ruido.
Funciones
Temas
Preprocesar datos de imágenes para deep learning
- Get Started with Image Preprocessing and Augmentation for Deep Learning
Preprocess data with deterministic operations such as normalization or color space conversion, or augment training data with randomized operations such as random cropping or color jitter.
- Datastores for Deep Learning (Deep Learning Toolbox)
Learn how to use datastores in deep learning applications. - Prepare Datastore for Image-to-Image Regression (Deep Learning Toolbox)
This example shows how to prepare a datastore for training an image-to-image regression network using thetransform
andcombine
functions ofImageDatastore
. - 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.
Crear redes neuronales para aplicaciones de procesamiento de imágenes
- 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. - 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. - Pretrained Deep Neural Networks (Deep Learning Toolbox)
Learn how to download and use pretrained convolutional neural networks for classification, transfer learning and feature extraction. - List of Deep Learning Layers (Deep Learning Toolbox)
Discover all the deep learning layers in MATLAB®.
Deep learning en MATLAB
- Deep Learning in MATLAB (Deep Learning Toolbox)
Discover deep learning capabilities in MATLAB using convolutional neural networks for classification and regression, including pretrained networks and transfer learning, and training on GPUs, CPUs, clusters, and clouds. - Semantic Segmentation Using Deep Learning (Computer Vision Toolbox)
This example shows how to train a semantic segmentation network using deep learning.