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Groupe Signal Image et Instrumentation
L’équipe s’intéresse aux domaines du traitement du signal et de l’image et de l’intelligence artificielle pour la mesure, l’instrumentation et le développement de capteurs, pour des applications en géophysique, en CND, SHM et biomédical.
L'équipe est rattachée au LAUM, Laboratoire d’Acoustique – Le Mans Université – CNRS – UMR6613.
Thématique de recherche : Contrôle Non-Destructif et «Structural Health Monitoring» ; Instrumentation biomédicale ; Capteurs optiques pour la mesure mécanique
Mots clés
Cascade de classifieurs
Transcranial Doppler ultrasound
Accelerométrie
Codalema
Classification
Artefact rejection
Entropy
Apprentissage automatique
Analyse du signal
Automatic scoring algorithm
Commande optimale
Animal–environment interaction
Machine Learning
Dairy cows
Palindromic vectors
Acoustoelasticity
Optimal command
Cluster Validity Index
Behaviour and movement
Nonlinear
Radio detection
Damage detection
Claudication
Algorithmes génétiques
9585Ry
Atrial fibrillation
Ischemia
Contrôle non-destructif
Intermittent claudication
Peripheral artery disease
Machine learning
Pathophysiology
Cow location
Accelerometry
Biomedical engineering
Nondestructive testing
CODALEMA
Binary sequence
Ultrasound
Spectrogram
Nonlinearity
Bidirectional arte- facts
Transcutaneous oxygen pressure
Comportement animal
Optimization
And stroke Obstructive sleep apnoea
Complexity
Cardiovascular disease
Clustering
Sleep apnea
Nonlinear Wave Modulation Spectroscopy
Composites materials
Transcutaneous oximetry
Bias control
Signal processing
Acoustic particle velocity
CR radiodetection
Genetic algorithm
Pulse rate variability
Microembolus
Gradient descent algorithm
Symmentropy
Artery
Artificial Neural Networks
Exercise oximetry
Acoustic Emission
Symmetry
Vache laitière
Symmetropy
Descriptor
Acoustic emission testing
Ankle brachial pressure index
Coda Wave Interferometry
Adaptive boosting
Cardiovascular risk
Algorithme d'apprentissage
Palindrome
Automatic sleep staging for polysomnography
Exercise testing
Beamforming
9640-z
Methods
Cluster analysis
Obstructive sleep apnea
9555Jz
Agro-ecology
Symptoms
Diagnosis
Chan-Vese
Calf pain
Arterial inflow
Behaviour classification
Concrete
Artificial Neural Networks ANNs
Microembolus detection
Structural health monitoring
Bruit de respiration
Accelerometer
Thoracic outlet syndrome
Agriculture
Les collaborations
Dernières publications
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Elsa Breton, Nicolas Savoye, Peggy Rimmelin-Maury, Benoit Sautour, Eric Goberville, et al.. Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT. Frontiers in Marine Science, 2023, 10, pp.12. ⟨10.3389/fmars.2023.1135446⟩. ⟨hal-04083118⟩