Object Detection

Getting Started with Object Detection Using Deep Learning (Computer Vision Toolbox)

Object detection using deep learning neural networks.

Augment Bounding Boxes for Object Detection

This example shows how to use MATLAB®, Computer Vision Toolbox™, and Image Processing Toolbox™ to perform common kinds of image and bounding box augmentation as part of object detection workflows.

Train Object Detector Using R-CNN Deep Learning

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

Import Pretrained ONNX YOLO v2 Object Detector

This example shows how to import a pretrained ONNX™(Open Neural Network Exchange) you only look once (YOLO) v2 [1] object detection network and use it to detect objects.

Export YOLO v2 Object Detector to ONNX

This example shows how to export a YOLO v2 object detection network to ONNX™ (Open Neural Network Exchange) model format.

Semantic Segmentation

Getting Started with Semantic Segmentation Using Deep Learning (Computer Vision Toolbox)

Segment objects by class using deep learning

Create Simple Semantic Segmentation Network in Deep Network Designer

This example shows how to create and train a simple semantic segmentation network using Deep Network Designer.

Augment Pixel Labels for Semantic Segmentation

This example shows how to use MATLAB®, Computer Vision Toolbox™, and Image Processing Toolbox™ to perform common kinds of image and pixel label augmentation as part of semantic segmentation workflows.

Semantic Segmentation Using Dilated Convolutions

Train a semantic segmentation network using dilated convolutions.

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.

Define Custom Pixel Classification Layer with Tversky Loss

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