Implement deep learning functionality in Simulink® models by using blocks from the Deep Neural Networks block library, included in the Deep Learning Toolbox™, or by using the Deep Learning Object Detector block from the Analysis & Enhancement block library included in the Computer Vision Toolbox™.
|Image Classifier||Classify data using a trained deep learning neural network|
|Predict||Predict responses using a trained deep learning neural network|
|Stateful Classify||Classify data using a trained deep learning recurrent neural network|
|Stateful Predict||Predict responses using a trained recurrent neural network|
|Deep Learning Object Detector||Detect objects using trained deep learning object detector|
This example shows how to classify an image in Simulink® using the
Image Classifier block.
This example shows how to use deep convolutional neural networks inside a Simulink® model to perform lane and vehicle detection.
This example shows how to use wavelet transforms and a deep learning network within a Simulink (R) model to classify ECG signals.
Import a pretrained TensorFlow™ network using
importTensorFlowNetwork, and then use the
Predict block for image classification in Simulink.
This example shows how to predict responses for a trained recurrent neural network in Simulink® by using the
Stateful Predict block.
This example shows how to classify data for a trained recurrent neural network in Simulink® by using the
Stateful Classify block.
Detect the presence of speech commands in audio using a Simulink model.
This example shows how to use an LSTM deep learning network inside a Simulink® model to predict the remaining useful life (RUL) of an engine.
Train a controller using reinforcement learning with a plant modeled in Simulink as the training environment.
Train a reinforcement learning agent for an adaptive cruise control application.
Train a reinforcement learning agent for a lane keeping assist application.
Train a reinforcement learning agent for a lane following application.
Generate C/C++ and GPU code for deployment on desktop or embedded targets