Deblurring with neural networks

This project is made for our signal class at Université Gustave Eiffel.

Requirements for the project

• Each project requires reading and understanding.

• Each project requires some coding (not only using some existing toolbox).

• Each project requires a testing phase of the methods on your own data.

Presentation

The duration of the presentation is 15/20 minutes.

~10-15 slides with the following wireframe :

• Title / name
• Presentation of the problem
• Proposed methods
• Theoretical analysis
• Numerical findings
• Critics
• Conclusion / perspective

Report

• You must bring a printed version with your to give me before the presentation. This is a strict deadline.
• Not less than 4 pages and up to 12 pages (A4, 11pt font, single column), including roughly one page of bibliography.
• Should be similar to a (short) scientific article.
• When presenting the numerics, give all parameters, so that the results are reproducible.
• It should not be a rewriting of the original article. You should only report about what you have done and only explain the theory that is relevant to explain the numerics you have done.
• Suggestion of structure for the report:
  • Abstract:
    • What problem(s) is studied ?
    • Why is it relevant ?
    • What solution(s) is proposed ?
    • Which contributions (theory, numerics, etc) ?
  • Introduction :
    • Presentation of the problem(s).
    • Previous works (at least a few citations). If relevant, include things that you have seen during the lectures.
    • Contributions. Why is the studied method different/better/worse/etc. than existing previous works.
  • Main body (~10 pages) :
    • Presentation of the method(s).
    • Theoretical guarantees.
    • Numerics.
  • Conclusion and perspective (~1 page)
    • Summary of the result obtained: pros and cons (limitation, problems, error in the articles, etc)
    • Possible improvement/extension
  • Bibliography (~1 page)

Get dataset

wget https://drive.google.com/uc?export=download&id=1P0mqAANuR-iGzfeYtKYczTH_Nd8-JoCW

Research papers