Coursebooks

Deep Learning for Optical Imaging

MICRO-723

Lecturer(s) :

Borhani Navid
Psaltis Demetri

Language:

English

Frequency

Every year

Summary

This course will focus on the practical implementation of artificial neural networks (ANN) using the open-source TensorFlow machine learning library developed by Google for Python.

Content

This course will focus on the practical implementation of artificial neural networks (ANN) using the open-source TensorFlow machine learning library developed by Google for Python. After a brief introduction to deep neural networks, the course will focus on the use and functionality of TensorFlow, and how it can be used to build models of different complexity for different types of optical imaging applications. Models will range from simple linear regression to convolutional neural networks (CNN) for image classification and mapping. The course will be assessed through coursework and group projects where the students will apply TensorFlow to specific machine learning applications.

Keywords

Deep learning, TensorFlow, Artificial neural networks, Imaging

Learning Prerequisites

Required courses

Proficiency in Python, basic optics

Recommended courses

MICRO-567 Optical Wave Proagation

Important concepts to start the course

Python familiarity, linear systems, basic optics

Learning Outcomes

By the end of the course, the student must be able to:

Teaching methods

1 hour/week  lecture 

1 hour/week interactive artificial neural network develoment for selected problems

 

 

 

 

Expected student activities

Attend lectures weekly

Attend exercise sessions

Participate in a class project 

Turn in homework every two weeks

 

 

 

 

Assessment methods

Homeworks

Project report

 

Resources

Bibliography

Tensor flow 

 

 

Notes/Handbook

Class notes will be posted on Moodle

In the programs

    • Semester
    • Exam form
       Multiple
    • Credits
      2
    • Subject examined
      Deep Learning for Optical Imaging
    • Lecture
      14 Hour(s)
    • Exercises
      14 Hour(s)
    • Practical work
      14 Hour(s)

Reference week

 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German