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深度学习调整

以编程方式调整训练选项，从检查点继续训练，并研究对抗示例

要了解如何使用 trainingOptions 函数设置选项，请参阅设置参数并训练卷积神经网络。在确定一些合适的开始选项后，您可以使用试验管理器自动扫描超参数或尝试贝叶斯优化。

通过生成对抗示例来研究网络稳健性。然后，您可以使用快速梯度符号方法 (FGSM) 对抗训练来训练在对抗扰动下保持稳健的网络。

App

深度网络设计器Design, visualize, and train deep learning networks

函数

trainingOptionsOptions for training deep learning neural network
trainNetworkTrain deep learning neural network

主题

设置参数并训练卷积神经网络

了解如何为卷积神经网络设置训练参数。

使用贝叶斯优化进行深度学习

此示例说明如何将贝叶斯优化应用于深度学习并找到卷积神经网络的最优网络超参数和训练选项。

并行训练深度学习网络

此示例说明如何在本地计算机上运行多个深度学习试验。使用此示例作为模板，您可以修改网络层和训练选项，以满足您的具体应用需要。无论您有一个还是多个 GPU，都可以使用这种方法。如果您只有一个 GPU，网络会在后台逐个进行训练。本示例中的方法使您能够在进行深度学习试验时继续使用 MATLAB®。

Train Network Using Custom Training Loop

This example shows how to train a network that classifies handwritten digits with a custom learning rate schedule.

Compare Activation Layers

This example shows how to compare the accuracy of training networks with ReLU, leaky ReLU, ELU, and swish activation layers.

Adapt Code Generated in Deep Network Designer for Use in Experiment Manager

Use Experiment Manager to tune the hyperparameters of a network trained in Deep Network Designer.

Deep Learning Tips and Tricks

Learn how to improve the accuracy of deep learning networks.

Train Robust Deep Learning Network with Jacobian Regularization

This example shows how to train a neural network that is robust to adversarial examples using a Jacobian regularization scheme [1].

相关信息

特色示例

Resume Training from Checkpoint Network

Resume Training from Checkpoint Network

Save checkpoint networks while training a deep learning network and resume training from a previously saved network.

打开实时脚本
Generate Untargeted and Targeted Adversarial Examples for Image Classification

Generate Untargeted and Targeted Adversarial Examples for Image Classification

Use the fast gradient sign method (FGSM) and the basic iterative method (BIM) to generate adversarial examples for a pretrained neural network.

打开实时脚本
Train Image Classification Network Robust to Adversarial Examples

Train Image Classification Network Robust to Adversarial Examples

Train a neural network that is robust to adversarial examples using fast gradient sign method (FGSM) adversarial training.

打开实时脚本
Train Robust Deep Learning Network with Jacobian Regularization

Train Robust Deep Learning Network with Jacobian Regularization

Train a neural network that is robust to adversarial examples using a Jacobian regularization scheme [1].

打开实时脚本

Deep Learning Toolbox 文档

支持

Introducing Deep Learning with MATLAB

Introducing Deep Learning with MATLAB

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