Artificial Intelligence

Apply machine learning and deep learning

Posts 1 - 10 of 147

R2024b: A Peek into New AI Features

MATLAB R2024b is the latest release and available for you to try. I am here to talk specifically about new AI features in the latest release, and if you're interested in other features, check out... 더 읽어보기 >>

Embedded AI Integration with MATLAB and Simulink 3

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... 더 읽어보기 >>

Simulate PyTorch and Other Python-Based Models with Simulink Co-Execution Blocks

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... 더 읽어보기 >>

Automating Visual Inspection with AI and PLC

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... 더 읽어보기 >>

Local LLMs with MATLAB 2

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... 더 읽어보기 >>

Export Models from Machine Learning Apps to Simulink

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... 더 읽어보기 >>

Explainability in Object Detection for MATLAB, TensorFlow, and PyTorch Models

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... 더 읽어보기 >>

Building Confidence in AI with Constrained Deep Learning

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,... 더 읽어보기 >>

Data Type Conversion Between MATLAB and Python: What’s New in R2024a 2

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... 더 읽어보기 >>

Verification and Validation for AI: From model implementation to requirements validation 1

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... 더 읽어보기 >>

Posts 1 - 10 of 147

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