Planning 2023
Course 2: Introduction to Neural Networks, Multilayer perceptron
Course 3: Convolutional Neural Nets
Course 4: Transformers for Vision
Course 5: Transfer learning and Domain adaptation
Course 6: Segmentation with CNN and Transformers
Course 7: Generative models with GANs
Course 8: Generative models (2): diffusion models
Course 9: Large VL models: CLIP, StableDiffusion, Flamingo
Course 10: controle de cours, sur tout ce que a été traité durant le cours, rien concernant les TPs.
Further reading (available at SorbonneU library):
Book Computer Vision: Algorithms and Applications, Richard Szeliski
Book Deep Learning, I. Goodfellow, Y. Bengio, A. Courville
Book Apprentissage artificiel : Concepts et algorithmes., A. Cornuéjols, L. Miclet
Book Machine Learning Techniques for Multimedia, M. Cord, P. Cunningham (Eds.)