Vos actions : Créer un document, voir la page générale.

Cultures numériques

Cours de Bachelor 1

Session de Travail 2


We make use of The Recognition Machine to make snapshots with algorithmic classifications of each student.

Classification is based on a technique called "deep learning" — a form of "machine learning" which itself fits into the broader history of Artificial Intelligence. The technique works by using "pre-trained models" : the software is able to quickly automatically label images. These outputs are based on (typically) thousands of examples of "training data" — other images that have been manually labelled with the desired outputs. We use two models, one for age & gender classification, and another for "emotion".


The emotion model is based on the popular FER2013 dataset which has a training set of nearly 30000 images that have been labelled according to the scheme :

  • 0 : Angry
  • 1 : Disgust
  • 2 : Fear
  • 3 : Happy
  • 4 : Sad
  • 5 : Surprise
  • 6 : Neutral

Questions are posed about the dataset : Who has collected these images, from where do they come from, who did the labelling ?



Antje shows polaroids from past workshops where participants self-describe themselves reflecting on the practices of colonial photography.

Finally we use The Recognition Machine to match input faces with faces in the archive (via faces from the dataset).

Par Guest, 10 décembre 2018