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

• Etienne Decencière
• Thomas Walter
• Santiago Velasco-Forero
• Samy Blusseau

Courses will take place at:

PariSanté Campus

2-10 rue Rue d'Oradour-sur-Glane 

75015 PARIS

Schedules and classrooms are available here: https://www.lamsade.dauphine.fr/wp/iasd/wp-content/uploads/sites/9/2023/09/edt_sept_2023.pdf

Courses will take place at:

PariSanté Campus (Classroom S 0.8)

2-10 rue Rue d'Oradour-sur-Glane 75015 PARIS

According to the following schedule:

The course material is available here:

https://cloud.minesparis.psl.eu/index.php/s/NHDJ89rj7zOCVDM

The course will be held at Mines Paris: 60 Bd. Saint-Michel (Paris 6ème). Classrooms are given in the timetable below.

Each session (except the first) will begin with two hours of lectures, followed by one hour of practical work. The students must bring their laptops with a configured WiFi access to eduroam.

Lessons and notebooks can be downloaded from:

https://cloud.mines-paristech.fr/index.php/s/I1O04oMRIqxbgZD