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Doctoral course

Topics in deep learning for perception, 3 credits

Course information

Research education subject

  • Computer Science

Course Syllabus

Course Syllabus


Course content

This course is intended as a guided study of deep neural network (NN) architectures applied to problems in perception research. We will overview the most common network designs and focus on applications relevant to perception with mobile robots. The course will cover:

  • An overview / revision of basic machine learning concepts relevant to deep learning
  • Deep feedforward networks
  • Autoencoders
  • Convolutional neural networks
  • Regularization and optimization for NNs
  • Practical tips for applying deep learning
  • Selected example deep NN approaches for perception problems