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Publications

Cette page présente les publications du Centre Borelli déposées sur le serveur HAL.

Affichage des publications 201 à 210 sur 1268 au total

Optimization and Control

Fixed Pattern Noise Removal For Multi-View Single-Sensor Infrared Camera

Fixed pattern noise (FPN) is a temporally coherent noise present on videos due to the non-uniformities in the response of the imaging sensor. It is a common problem for infrared videos which degrades the quality of the observation and hinders…

Hortensia Barral, Pablo Arias, Axel Davy

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) -

Mathematics

A sparse exponential family latent block model for co-clustering

Over the last decades, co-clustering models have spawned a number of algorithms showing the advantages that co-clustering can have over clustering. This is especially true for sparse high-dimensional data such as document-word matrices, which are…

Saeid Hoseinipour, Mina Aminghafari, Adel Mohammadpour, Mohamed Nadif

Advances in Data Analysis and Classification -

Computer Science

PDB Unet: A spatio temporal video Fixed Pattern Noise removal network

In this paper we propose a novel video non uniformity correction algorithm based on a convolutional neural network. Fixed pattern noise (FPN) is a temporally coherent noise present on videos due to the non-uniformities of the sensors that can…

Hortensia Barral, Pablo Arias, Axel Davy

European Conference on Computer Vision (ECCV) 2024 - Advances in Image Manipulation workshop -

Artificial Intelligence

Pattern detection and shape analysis for physiological timeseries

Time series are prevalent in biomedical applications where they frequently display recurring or abnormal patterns that hold significant information for statistical analysis. A notable example is the heartbeat in electrocardiograms, a recurring…

Thibaut Germain

Artificial Intelligence

Structured Loss for Deep Change-Point Detection

Change-point detection, which is finding abrupt changes in the behaviour of a signal, is a crucial step in numerous data processing pipelines. There are many available algorithms in the literature; choosing one and calibrating it is complex and time…

Simon Blotas, Charles Truong

32nd European Signal Processing Conference (EUSIPCO) -

Computer Science

Une variante pondérée de K-means adaptée aux données textuelles

This article proposes a weighted variant of the K-means algorithm, specifically adapted to textual data. The algorithm aims to improve clustering performance and interpretability by assigning weights to the most discriminating features for each…

Amine Ferdjaoui, Séverine Affeldt, Mohamed Nadif

29èmes Rencontres de la Société Francophone de Classification -