Embedded AI, that is the integration of artificial intelligence and embedded systems, enables devices to process data and make decisions locally. It enhances efficiency, reduces latency, and... 更多内容 >>

This blog post is from Maggie Oltarzewski, Product Marketing Engineer at MathWorks. In R2024a, four new blocks for co-executing deep learning models in Simulink were added to Deep Learning... 更多内容 >>

The following post is from Sagar Hukkire, application engineer for AI, and Conrado Ramirez Garcia, application engineer for design automation and code generation. Visual inspection is the... 更多内容 >>

Local large language models (LLMs), such as llama, phi3, and mistral, are now available in the Large Language Models (LLMs) with MATLAB repository through Ollama™! This is such exciting news that I... 更多内容 >>

In this blog post, I am going to show you the most interactive way to create a Simulink model that includes a machine learning model by using the Classification Learner app. Simulating and testing... 更多内容 >>

In R2024a, Deep Learning Toolbox Verification Library introduced the d-rise function. D-RISE is an explainability tool that helps you visualize and understand  which parts are important for object... 更多内容 >>

Constrained deep learning is an advanced approach to training robust deep neural networks by incorporating constraints into the learning process. These constraints can be based on physical laws,... 更多内容 >>

When combining MATLAB with Python® to create deep learning workflows, data type conversion between the two frameworks can be time consuming and sometimes perplexing. I 've certainly experimented... 更多内容 >>

The following post is from Lucas García, Product Manager for Deep Learning Toolbox. This is the fourth and final post of our Verification and Validation for AI post series. Check out our... 更多内容 >>

In this blog post we are going to show you how to use the newest MATLAB functions to: Import models from TensorFlow and PyTorch into MATLAB Export models from MATLAB to TensorFlow and... 更多内容 >>