The sliding singular spectrum analysis: A data-driven nonstationary signal decomposition tool J Harmouche, D Fourer, F Auger, P Borgnat, P Flandrin IEEE Transactions on Signal Processing 66 (1), 251-263, 2017 | 145 | 2017 |
Chirp rate and instantaneous frequency estimation: Application to recursive vertical synchrosqueezing D Fourer, F Auger, K Czarnecki, S Meignen, P Flandrin IEEE Signal Processing Letters 24 (11), 1724-1728, 2017 | 110 | 2017 |
Multivariate event detection methods for non-intrusive load monitoring in smart homes and residential buildings S Houidi, F Auger, HBA Sethom, D Fourer, L Miègeville Energy and Buildings 208, 109624, 2020 | 46 | 2020 |
Second-order time-reassigned synchrosqueezing transform: Application to draupner wave analysis D Fourer, F Auger 2019 27th European signal processing conference (EUSIPCO), 1-5, 2019 | 40 | 2019 |
The ASTRES toolbox for mode extraction of non-stationary multicomponent signals D Fourer, J Harmouche, J Schmitt, T Oberlin, S Meignen, F Auger, ... 2017 25th European Signal Processing Conference (EUSIPCO), 1130-1134, 2017 | 40 | 2017 |
Recursive versions of the Levenberg-Marquardt reassigned spectrogram and of the synchrosqueezed STFT D Fourer, F Auger, P Flandrin 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 39 | 2016 |
On the use of concentrated time–frequency representations as input to a deep convolutional neural network: Application to non intrusive load monitoring S Houidi, D Fourer, F Auger Entropy 22 (9), 911, 2020 | 37 | 2020 |
A fast time-frequency multi-window analysis using a tuning directional kernel K Czarnecki, D Fourer, F Auger, M Rojewski Signal Processing 147, 110-119, 2018 | 31 | 2018 |
Automatic timbre classification of ethnomusicological audio recordings D Fourer, JL Rouas, P Hanna, M Robine International Society for Music Information Retrieval Conference (ISMIR 2014), 2014 | 31 | 2014 |
Local AM/FM parameters estimation: Application to sinusoidal modeling and blind audio source separation D Fourer, F Auger, G Peeters IEEE Signal Processing Letters 25 (10), 1600-1604, 2018 | 27 | 2018 |
Comparative evaluation of non-intrusive load monitoring methods using relevant features and transfer learning S Houidi, D Fourer, F Auger, HBA Sethom, L Miègeville Energies 14 (9), 2726, 2021 | 22 | 2021 |
L’UNIVERSITÉ BORDEAUX D FOURER Université Bordeaux 1, 2013 | 19 | 2013 |
Deep learning methods for MRI brain tumor segmentation: a comparative study I Brahim, D Fourer, V Vigneron, H Maaref 2019 Ninth International Conference on Image Processing Theory, Tools and …, 2019 | 18 | 2019 |
Statistical assessment of abrupt change detectors for non-intrusive load monitoring S Houidi, F Auger, HBA Sethom, L Miègeville, D Fourer, X Jiang 2018 IEEE International Conference on Industrial Technology (ICIT), 1314-1319, 2018 | 16 | 2018 |
DReaM: a novel system for joint source separation and multi-track coding S Marchand, R Badeau, C Baras, L Daudet, D Fourer, L Girin, S Gorlow, ... AES 2012-133rd AES Convention, CD 133papers, 2012 | 16 | 2012 |
Fast and adaptive blind audio source separation using recursive Levenberg-Marquardt synchrosqueezing D Fourer, G Peeters 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 14 | 2018 |
Design of an electricity consumption measurement system for Non Intrusive Load Monitoring S Houidi, F Auger, P Frétaud, D Fourer, L Miègeville, HBA Sethom 2019 10th international renewable energy congress (IREC), 1-6, 2019 | 13 | 2019 |
A novel pseudo-Bayesian approach for robust multi-ridge detection and mode retrieval Q Legros, D Fourer 2021 29th European Signal Processing Conference (EUSIPCO), 1925-1929, 2021 | 12 | 2021 |
Methods and datasets for DJ-mix reverse engineering D Schwarz, D Fourer Perception, Representations, Image, Sound, Music: 14th International …, 2021 | 12 | 2021 |
Relevant feature selection for home appliances recognition S Houidi, F Auger, HBA Sethom, D Fourer, L Miègeville Electrimacs 2017, 2017 | 10 | 2017 |