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Concept

Annotation automatique d'images

Publications associées (25)

Theoretical foundations of forward feature selection methods based on mutual information

Francisco Santos Paredes Quartin de Macedo

Feature selection problems arise in a variety of applications, such as microarray analysis, clinical prediction, text categorization, image classification and face recognition, multi-label learning, and classification of internet traffic. Among the various ...

ELSEVIER SCIENCE BV2019

Multimodal person recognition in audio-visual streams

Do Hoang Nam Le

Multimedia databases are growing rapidly in size in the digital age. To increase the value of these data and to enhance the user experience, there is a need to make these videos searchable through automatic indexing. Because people appearing and talking in ...

EPFL2019

A Geometry-Inspired Decision-Based Attack

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli

Deep neural networks have recently achieved tremendous success in image classification. Recent studies have however shown that they are easily misled into incorrect classification decisions by adversarial examples. Adversaries can even craft attacks by que ...

IEEE COMPUTER SOC2019

Deep neural networks for plasma tomography with applications to JET and COMPASS

Yiming Li, Olivier Sauter, Richard Pitts, Ambrogio Fasoli, Basil Duval, Henri Weisen, Yann Camenen, Jan Horacek, Javier García Hernández, Duccio Testa, Marco Wischmeier, Nicola Vianello, Mikhail Maslov, Patrick Blanchard, Alessandro Pau, Davide Galassi, Federico Alberto Alfredo Felici, Antonio José Pereira de Figueiredo, Cristian Sommariva, Jonathan Graves, Emiliano Fable, Dalziel Joseph Wilson, Francesca Maria Poli, Antoine Pierre Emmanuel Alexis Merle, Federico Nespoli, Daniele Brunetti, Anna Teplukhina, Hamish William Patten, Samuel Lanthaler, Haomin Sun, Alberto Mariani, Michele Marin

Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural network ...

2019

Learning to See through Reflections

Sabine Süsstrunk

"Pictures of objects behind a glass are difficult to interpret" "and understand due to the superposition of two real images: a reflection layer and a background layer. Separation of these two layers is challenging due to the ambiguities in as- signing text ...

IEEE2018