Deep learning for image analysis

Author

Agustin Corbat / Bruno Vellutini

Published

January 7, 2026

TipLearning Objectives

By the end of this session, you will be able to:

  • Be aware of how machine and deep learning work
  • Know where to look for models and tools that can be used
  • Understand deep learning and neural network fundamentals
  • Explain how convolutional networks learn spatial features
  • Understand machine learning principles for image classification
  • Explain how pixel classification differs from deep learning
  • Use tools like ilastik, WEKA, and APOC for interactive classification
  • Recognize when machine learning is appropriate versus classical methods

Slides

Materials

Corbat, A. A., & Vellutini, B. (2026). 3D segmentation using machine/deep learning. Light-Sheet Image Analysis Workshop 2026 (LiSIAW2026), Santiago, Chile. Zenodo. https://doi.org/10.5281/zenodo.18155250