Use Deep Network Designer to generate MATLAB code to construct and train a network.
Use MATLAB Coder™ or GPU Coder™ together with Deep Learning Toolbox™ to generate C++ or CUDA code and deploy convolutional neural networks on embedded platforms that use Intel®, ARM®, or NVIDIA® Tegra® processors.
Generate MATLAB Code from Deep Network Designer
Generate MATLAB code to recreate designing and training a network in Deep Network Designer.
Deep Learning with GPU Coder (GPU Coder)
Generate CUDA code for deep learning neural networks
Code Generation for Deep Learning Networks
This example shows how to perform code generation for an image classification application that uses deep learning.
Code Generation for a Sequence-to-Sequence LSTM Network
This example demonstrates how to generate CUDA® code for a long short-term memory (LSTM) network.
Deep Learning Prediction on ARM Mali GPU
This example shows how to use the cnncodegen
function to generate code for an image classification application that uses deep learning on ARM® Mali GPUs.
Code Generation for Object Detection by Using YOLO v2
This example shows how to generate CUDA® MEX for a you only look once (YOLO) v2 object detector.
Lane Detection Optimized with GPU Coder
This example shows how to generate CUDA® code from a deep learning network, represented by a SeriesNetwork
object.
Integrating Deep Learning with GPU Coder into Simulink
This example shows how to integrate the CUDA® code generated for a deep learning network into Simulink®.
Deep Learning Prediction by Using NVIDIA TensorRT
This example shows code generation for a deep learning application by using the NVIDIA TensorRT™ library.
Deep Learning Prediction by Using Different Batch Sizes
This example demonstrates code generation with batch sizes greater than 1.
Traffic Sign Detection and Recognition
This example shows how to generate CUDA® MEX code for a traffic sign detection and recognition application that uses deep learning.
This example shows code generation for a logo classification application that uses deep learning.
This example shows code generation for pedestrian detection application that uses deep learning.
Code Generation for Denoising Deep Neural Network
This example shows how to generate CUDA® MEX from MATLAB® code and denoise grayscale images by using the denoising convolutional neural network (DnCNN [1]).
Code Generation for Semantic Segmentation Network
This example shows code generation for an image segmentation application that uses deep learning.
Train and Deploy Fully Convolutional Networks for Semantic Segmentation
This example shows how to train and deploy a fully convolutional semantic segmentation network on an NVIDIA® GPU by using GPU Coder™.
Code Generation for Semantic Segmentation Network by Using U-net
This example shows code generation for an image segmentation application that uses deep learning.
Deep Learning Prediction on ARM Mali GPU (GPU Coder)
This example shows how to use the cnncodegen
function to generate code for an image classification application that uses deep learning on ARM® Mali GPUs.
Code Generation for a Sequence-to-Sequence LSTM Network (GPU Coder)
This example demonstrates how to generate CUDA® code for a long short-term memory (LSTM) network.
Code Generation for Deep Learning on ARM Targets
This example shows how to generate and deploy code for prediction on an ARM®-based device without using a hardware support package.
Code Generation for Deep Learning on Raspberry Pi
This example shows how to generate and deploy code for prediction on a Raspberry Pi™ by using codegen
with the MATLAB Support Package for Raspberry Pi Hardware.
Deep Learning Prediction with ARM Compute Using cnncodegen
This example shows how to use cnncodegen
to generate code for a Logo classification application that uses deep learning on ARM® processors.
Deep Learning Prediction with Intel MKL-DNN
This example shows how to use codegen
to generate code for an image classification application that uses deep learning on Intel® processors.
Generate C++ Code for Object Detection Using YOLO v2 and Intel MKL-DNN
This example shows how to generate C++ code for the YOLO v2 Object detection network on an Intel® processor.
Code Generation and Deployment of MobileNet-v2 Network to Raspberry Pi
This example shows how to generate and deploy C++ code that uses the MobileNet-v2 pretrained network for object prediction.
Code Generation for Semantic Segmentation Application on Intel CPUs That Uses U-Net (MATLAB Coder)
Generate a MEX function that performs image segmentation by using the deep learning network U-Net on Intel CPUs.
Code Generation for LSTM Network on Raspberry Pi (MATLAB Coder)
Generate code for a pretrained long short-term memory network to predict Remaining Useful Life (RUI) of a machine.
Cross Compile Deep Learning Code for ARM Neon Targets (MATLAB Coder)
Generate library or executable code on host computer for deployment on ARM hardware target.
Load Pretrained Networks for Code Generation (MATLAB Coder)
Create a SeriesNetwork
, DAGNetwork
,
yolov2ObjectDetector
, or ssdObjectDetector
object for code generation.
Deep Learning with MATLAB Coder (MATLAB Coder)
Generate C++ code for deep learning neural networks (requires Deep Learning Toolbox)