Cours

CS-442: Computer vision

Résumé

Computer Vision aims at modeling the world from digital images acquired using video or infrared cameras, and other imaging sensors.

We will focus on images acquired using digital cameras. We will introduce basic processing techniques and discuss their field of applicability.

Séances de cours

Enseignant·e

Pascal Fua

Pascal Fua received an engineering degree from Ecole Polytechnique, Paris, in 1984 and the Ph.D. degree in Computer Science from the University of Orsay in 1989. He then worked at SRI International and INRIA Sophia-Antipolis as a Computer Scientist. He joined EPFL in 1996 where he is now a Professor in the School of Computer and Communication Science and heads the Computer Vision Laboratory. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and machine learning. He has (co)authored over 300 publications in refereed journals and conferences. He is an IEEE Fellow and has been an Associate Editor of IEEE journal Transactions for Pattern Analysis and Machine Intelligence. He often serves as program committee member, area chair, and program chair of major vision conferences and has cofounded three spinoff companies (Pix4D, PlayfulVision, and NeuralConcept).

Source officielle

https://edu.epfl.ch/coursebook/fr/computer-vision-CS-442

Page Moodle

http://go.epfl.ch/CS-442

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Résumé

Computer Vision aims at modeling the world from digital images acquired using video or infrared cameras, and other imaging sensors.

We will focus on images acquired using digital cameras. We will introduce basic processing techniques and discuss their field of applicability.

Séances de cours

Enseignant·e

Pascal Fua

Source officielle

https://edu.epfl.ch/coursebook/fr/computer-vision-CS-442

Page Moodle

http://go.epfl.ch/CS-442

Séances de ce cours (31)

CS-442 Summer 2024

Formation d'image: Comprendre les projections 2D à partir de scènes 3D

Explique les principes de la formation d'images, couvrant la projection de la lumière, la numérisation et le modèle de caméra sténopé.

Deep Learning : Détection de périphérie et réseaux neuronaux

Discute des techniques de détection de bord et de l'évolution de l'apprentissage profond dans les réseaux neuronaux.

CS-442 Summer 2024

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