Computer Vision Using Deep Learning

Extend deep learning workflows with computer vision applications

Apply deep learning to computer vision applications by using Deep Learning Toolbox™ together with Computer Vision Toolbox™.

Topics

Object Detection Using YOLO v2 Deep Learning

This example shows how to train an object detector using a deep learning technique named you only look once (YOLO) v2.

Semantic Segmentation Using Deep Learning

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

Semantic Segmentation of Multispectral Images Using Deep Learning

This example shows how to train a U-Net convolutional neural network to perform semantic segmentation of a multispectral image with seven channels: three color channels, three near-infrared channels, and a mask.

3-D Brain Tumor Segmentation Using Deep Learning

This example shows how to train a 3-D U-Net neural network and perform semantic segmentation of brain tumors from 3-D medical images.

Semantic Segmentation Using Dilated Convolutions

This example shows how to train a semantic segmentation network using dilated convolutions.

Define Custom Pixel Classification Layer with Dice Loss

This example shows how to define and create a custom pixel classification layer that uses Dice loss.

Object Detection Using Deep Learning

This example shows how to train an object detector using deep learning and R-CNN (Regions with Convolutional Neural Networks).

Object Detection Using Faster R-CNN Deep Learning

This example shows how to train an object detector using a deep learning technique named Faster R-CNN (Regions with Convolutional Neural Networks).

Featured Examples