How to Perform Deep Learning Inference in Simulink ?

To perform deep learning inference in Simulink, you can use the following steps:

Import the pre-trained deep learning model into Simulink. You can do this by using the Deep Learning Toolbox block library.

Configure the input and output ports of the deep learning model. The input ports should be connected to the data that the model will be trained on. The output ports should be connected to the data that the model will generate.

Run the Simulink model. This will cause the deep learning model to be trained on the data that is connected to the input ports.

Once the deep learning model has been trained, you can use it to perform inference on new data. To do this, simply connect the new data to the input ports of the model and run the Simulink model again.

Here are some additional tips for performing deep learning inference in Simulink:

Use a GPU to speed up the inference process. GPUs are much faster than CPUs for performing deep learning inference.

Use a pre-trained model. Pre-trained models are a great way to get started with deep learning inference. They have already been trained on a large dataset of data, so you can use them to perform inference on new data without having to train the model yourself.

Use a validation set. A validation set is a set of data that is not used to train the deep learning model. It is used to evaluate the performance of the model on new data.

Use a cross-validation set. A cross-validation set is a set of data that is used to both train and evaluate the deep learning model. This can help to improve the performance of the model on new data.

Learn how to import and use a pretrained neural network in Simulink® using blocks provided by Computer Vision Toolbox™ and Deep Learning Toolbox™. Follow an example workflow of using an object detection network to predict object locations for a given input video. You will learn how to import a video, how to store and use a neural network to make predictions, how to calculate the speed with which a model performs, and how you can display a neural network’s predictions right in Simulink.  

 

- The Deep Learning Object Detector block is provided as part of Computer Vision Toolbox: https://bit.ly/3L2SjY0  

- Learn more about deep learning in Simulink here: https://bit.ly/3IWTtBJ 

- The Simulink model shown in this video, as well as all code for the Deep Learning for Object Detection Series, can be found in this repository: http://bit.ly/3IUGdgZ  

 

Video Chapters:  

0:00 Introduction  

0:34 The Input Video 

1:06 Overview of the Simulink Model 

3:29 Running the simulation and viewing results 

4:07 Conclusion