Automated Labeling and Iterative Learning for Signals

Date Time
29 Jul 2021
5:30 AM EDT
29 Jul 2021
9:00 AM EDT
29 Jul 2021
2:00 PM EDT


Labeling signal data is very important step in creating AI-based signal processing solutions. However, this step can be very time-consuming and manual.

In this session, we introduce signal labeling for use in AI applications and discuss how MATLAB can be used to speed up and  simplify the process. We describe the use of preprocessing to extract information from signals. The session will cover different approaches for signal labeling including using algorithms and automating with deep learning models. We will also discuss an iterative method of building deep learning models and reduce human effort in labeling.

Highlights include:

  • Using and extending the Signal Labeler app
  • Preprocessing to facilitate signal labeling
  • Iteratively building and incorporating deep learning models
  • Automating signal labeling

Please allow approximately 45 minutes to attend the presentation and Q&A session. We will be recording this webinar, so if you can't make it for the live broadcast, register and we will send you a link to watch it on-demand.

About the Presenter

Esha Shah is a Product Manager at MathWorks focusing on Signal Processing and Wavelets Toolbox. She supports MATLAB users focusing on advanced signal processing and AI workflows. Before joining MathWorks, she received her Master’s in Engineering Management from Dartmouth College and Bachelor’s in Electronics and Telecommunication Engineering from Pune University, India.

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