深度学习
您可以将 Simulink® Coder™ 与 Deep Learning Toolbox™ 结合使用,从经过训练的卷积神经网络 (CNN) 生成代码。深度学习使用卷积神经网络 (CNN) 直接从图像中学习有用的数据表示。您可以将生成的代码部署到使用 Intel® 或 ARM® 处理器的嵌入式平台。您还可以从不依赖任何第三方库的经过训练的 CNN 生成泛型 C 或 C++ 代码。
主题
- Workflow for Deep Learning C/C++ Code Generation for Simulink Models
Overview of C/C++ code generation workflow for deep learning neural networks.
- Generate Code for Deep Learning Networks Using MATLAB Function Block
Generate code for a model containing a MATLAB Function block that uses the GoogLeNet trained deep learning network.
- Generate Code for Blocks from Deep Neural Networks Library
Generate code for a model containing the GoogLeNet trained deep learning network.
- Code Generation for Deep Learning Simulink Model That Performs Lane and Vehicle Detection
This example shows how to generate C++ code from a Simulink® model that performs lane and vehicle detection using convolutional neural networks (CNN).
- Generate Generic C/C++ for Sequence-to-Sequence Deep Learning Simulink Models
Generate C/C++ code for a sequence-to-sequence deep learning Simulink model.
- Code Generation for Detect Defects on Printed Circuit Boards Using YOLOX Network
Generate code for a You Only Look Once X (YOLOX) object detector that can detect, localize, and classify defects in printed circuit boards (PCBs). (自 R2023b 起)
- Generate Generic C Code Using The Stateful Predict Block in Simulink
This example shows how to generate generic C code using the Stateful Predict block and the SIL workflow. (自 R2024a 起)
相关信息
- Simulink 深度学习 (Deep Learning Toolbox)
- 使用 MATLAB Coder 进行深度学习