This is an old revision of the document!


Deep Learning for Image Analysis

Deep learning has achieved formidable results in the image analysis field in recent years, in many cases exceeding human performance. This success opens paths for new applications, entrepreneurship and research, while making the field very competitive.

This course aims at providing the students with the theoretical and practical basis for understanding and using deep learning for image analysis applications.

Lecturers

Winter 2020 edition: IASD Master

Teaching assistants

  • David Duque
  • Leonardo Gigli
  • Arthur Imbert
  • Tristan Lazard

Fall 2019 Edition: ATHENS MP10

Invited speakers

  • Marc Huertas (Canaries Astrophysics Institute; Observatoire de Paris)
  • Maximilian Jaritz (Valeo.ai)
  • Olivier Moindrot (Owkin)
  • Bogdan Stanciulescu (CAOR, MINES ParisTech)

Teaching assistants

  • Eric Bazan
  • David Duque
  • Leonardo Gigli
  • Arthur Imbert
  • Tristan Lazard

Fall 2018 Edition: ATHENS MP10

Invited speakers

  • Pierre Fillard (Therapixel)
  • Marc Huertas-Company (Canaries Astrophysics Institute; Observatoire de Paris)
  • Bogdan Stanciulescu (CAOR, MINES ParisTech)
  • Pauline Luc (Facebook AI Research)

Teaching assistants

  • Robin Alais
  • Joseph Boyd
  • Leonardo Gigli
  • Peter Naylor
  • Robin Alais
start.1582823064.txt.gz · Last modified: 2020/02/27 18:04 by edecenciere
CC Attribution-Share Alike 4.0 International
Driven by DokuWiki Recent changes RSS feed Valid CSS Valid XHTML 1.0