Sự Kiện

This series will look at two current trends affecting mining companies: the need to improve energy efficiency in order to reduce carbon emissions, and the growing benefits of autonomous mine operations. You will hear from experts in the field and MathWorks Australia engineers about the innovations and practical frameworks you can use to address these trends in your own operations.

Pose estimation and localization are critical components for both autonomous systems and systems that require perception for situational awareness. Fusing data from multiple sensors and applying fusion filters is a typical workflow required for accurate localization.

In this webinar, we will demonstrate a real-world medical application of an ECG analysis and show how you can use MATLAB & Simulink to train and verify AI models. You will learn some basic and advanced techniques in order to fully utilize the benefits of machine learning in biomedical signal analysis.

This webinar will demonstrate statistical and machine learning techniques in MATLAB on real-world datasets to monitor manufacturing processes and detect equipment anomalies.

Artificial Intelligence (AI) is bringing a drastic change in technological fields, where it can be implemented to automate the system for more efficiency and performance. AI is now getting used in multiple fields from simply your mobile phone to diagnosing the diseases providing a high-performance and accurate system work with efficiency. In this webinar, you will see the workflow of artificial intelligence that can be implement in the industry. The workflow spans from data preparation to the deployment of the algorithm in real life application.

MATLAB® and Simulink® with deep learning frameworks, TensorFlow and PyTorch, provide enhanced capabilities for building and training your machine learning models. Via interoperability, you can take full advantage of the MATLAB ecosystem and integrate it with resources developed by the open-source community. You can combine workflows that include data-centric preprocessing, model tuning, model compression, model integration, and automatic code generation with models developed outside of MATLAB.

Learn how synthesized radar data can be used to improve your design choices, how design models can be shared across organizations, and how testing data can be used to shorten integration cycles.

Discover how to use Model-Based Design with MATLAB® and Simulink® for Automotive/EV/ADAS in this workshop session.

MATLAB provides flexible, two-way integration with many programming languages, including Python. This allows different teams to work together and use MATLAB algorithms within production software and IT systems. This webinar will cover how to call MATLAB from Python and how to call Python libraries from MATLAB.