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image for course Signal Segmentation with Deep Learning

Signal Segmentation with Deep Learning

Build upon your signal classification skills by learning to segment a signal using the sequence-to-sequence workflow. Use deep networks to classify each time step of a signal instead of one class for an entire signal. Learn how to label and visualize regions within a signal, then adjust the training process to output a sequence of classes.

Course modules

Introduction

Get an overview of the course.

Lessons:
  • Course Overview
  • Outline and Learning Outcomes
  • Course Example: Classify Regions of Flooding Levels

Label Regions of Interest

Learn two different ways to label time steps in a signal. Label time steps in a signal by importing a sequence of labels from a file and using the Signal Labeler app.

Lessons:
  • Use Labels from a File
  • Walkthrough of Signal Labeler
  • Use Signal Labeler
  • Use Labels from Signal Labeler

Classify Each Time Step of Signal Data

Create a deep network architecture that can classify one label for each time step of a signal. Train and evaluate a deep network using specialized visualizations.

Lessons:
  • Create Sequence-to-Sequence Architecture
  • Train a Sequence-to-Sequence Classification Network
  • View Misclassified Regions

Conclusion

Learn next steps and give feedback on the course.

Lessons:
  • Summary
  • Additional Resources
  • Survey

Format:Self-paced

Language:English

Language

  • Hands-on exercises with automated feedback
  • Access to MATLAB through your web browser
  • Shareable progress report and course certificate

Signal Processing Onramp

An interactive introduction to signal processing methods for spectral analysis.

Machine Learning Onramp

Learn the basics of practical machine learning methods for classification problems.

Signal Classification with Deep Learning

Learn the workflow for classifying signals with deep networks.

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