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深度学习在计算机视觉领域的应用

利用计算机视觉应用扩展深度学习工作流

通过将 Computer Vision Toolbox™ 与 Deep Learning Toolbox™ 结合使用,将深度学习应用于计算机视觉应用。

App

图像标注器Label images for computer vision applications
视频标注器Label video for computer vision applications

函数

boxLabelDatastoreDatastore for bounding box label data
pixelLabelDatastoreDatastore for pixel label data
pixelLabelImageDatastoreDatastore for semantic segmentation networks

主题

目标检测

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 perform common kinds of image and bounding box augmentation as part of object detection workflows.

使用 R-CNN 深度学习训练目标检测器

此示例说明如何使用深度学习和 R-CNN(区域卷积神经网络)训练目标检测器。

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.

语义分割

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

Segment objects by class using deep learning.

Train 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 perform common kinds of image and pixel label augmentation as part of semantic segmentation workflows.

使用扩张卷积进行语义分割

使用扩张卷积训练语义分割网络。

使用深度学习对多光谱图像进行语义分割

此示例说明如何使用 U-Net 对包含七个通道的多光谱图像执行语义分割。

使用深度学习进行三维脑肿瘤分割

此示例说明如何基于三维医学图像训练三维 U-Net 神经网络,并执行脑肿瘤的语义分割。

定义使用 Tversky 损失的自定义像素分类层

此示例说明如何定义和创建使用 Tversky 损失的自定义像素分类层。

Explore Semantic Segmentation Network Using Grad-CAM

This example shows how to explore the predictions of a semantic segmentation network using Grad-CAM.

特色示例