Sự Kiện

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.

Explore how to increase productivity using Apps for design and analysis. Deep Neural Networks are becoming a ubiquitous tool for all industries particularly the computer vision applications of Machine Learning. Learn how Deep Learning is used in industries such as biomedicine, industrial automation.

In this webinar, MathWorks will demonstrate a workflow that provides system-level electrical loading information to inform an electrical system design task. The electrical system in this case will be a parallel-connected fuel-cell stack and battery energy storage system. The aim of the electrical design is to develop the most efficient power supply to meet the needs of a given drive cycle. The electrical design is then evaluated in a full-system level model.

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.

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.

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

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.

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.

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.