Mauro DALLA MURA
Maître de conférences Grenoble-INP
Equipe SIGnal iMAge PHYsique
Département Images et Signal
ME CONTACTER / CONTACT ME
Mail : mauro.dalla-mura@gipsa-lab.grenoble-inp.fr

11 rue des mathématiques
Domaine Universitaire
BP 46
38402 Saint Martin d'Hères cedex

Bureau D1137
Tél.33 (0)4 76 82 64 82
Fax : 33 (0)4 76 57 47 90
PUBLICATIONS RECENTES / RECENT PUBLICATIONS
Les derniéres publications de la collection Gipsa dans HAL

Some issues in computing the CP decomposition of NonNegative Tensors

Pierre Comon, Mohamad Jouni, Mauro Dalla Mura. Some issues in computing the CP decomposition of NonNegative Tensors. 14th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2018), Jul 2018, Univ. of Surrey, Guildford, United Kingdom. Springer, Latent Variable Analysis and Signal Separation, 10891, Theoretical Computer Science and General Issues. 〈hal-01784370〉

Use of deep features for the automatic classification of fish sounds

Marielle Malfante, Omar Mohammed, Cedric Gervaise, Mauro Dalla Mura, Jerome Mars. Use of deep features for the automatic classification of fish sounds. OCEANS'18 MTS/IEEE, May 2018, Kobe, Japan. 〈hal-01802551〉

Automatic fish sounds classification

Marielle Malfante, Jerome Mars, Mauro Dalla Mura, Cedric Gervaise. Automatic fish sounds classification. Journal of the Acoustical Society of America, Acoustical Society of America, 2018, 143 (5), pp.2834 - 2846. 〈10.1121/1.5036628〉. 〈hal-01791774〉

Machine Learning for Volcano-Seismic Signals: Challenges and Perspectives

Marielle Malfante, Mauro Dalla Mura, Jean-Philippe Métaxian, Jerome Mars, Orlando Macedo, et al.. Machine Learning for Volcano-Seismic Signals: Challenges and Perspectives. IEEE Signal Processing Magazine, Institute of Electrical and Electronics Engineers, 2018, 35 (2), pp.20 - 30. 〈10.1109/MSP.2017.2779166〉. 〈hal-01742506〉

GPU Framework for Change Detection in Multitemporal Hyperspectral Images

Javier López-Fandiño, Dora B. Heras, Francisco Argüello, Mauro Dalla Mura. GPU Framework for Change Detection in Multitemporal Hyperspectral Images. International Journal of Parallel Programming, Springer Verlag, 2017, 〈10.1007/s10766-017-0547-5〉. 〈hal-01666058〉

Multimorphological Superpixel Model for Hyperspectral Image Classification

Tianzhu Liu, Yanfeng Gu, Jocelyn Chanussot, Mauro Dalla Mura. Multimorphological Superpixel Model for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2017, 55 (12), pp.6950 - 6963. 〈10.1109/TGRS.2017.2737037〉. 〈hal-01665290〉

Apprentissage statistique: classification automatique de signaux volcano-sismiques

Marielle Malfante, Mauro Dalla Mura, Baptiste Boullay, Jean-Philippe Métaxian, Jerome Mars. Apprentissage statistique: classification automatique de signaux volcano-sismiques. XXVIème colloque GRETSI (GRETSI 2017), Sep 2017, Juan-Les-Pins, France. 2017 - GRETSI - Actes de Colloque, 2017, Proceeding Actes de la conférence Gretsi 2017. 〈hal-01583748〉

Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks

Rasha Alshehhi, Prashanth Reddy Marpu, Wei Lee Woon, Mauro Dalla Mura. Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks. ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier, 2017, 130, pp.139 - 149. 〈10.1016/j.isprsjprs.2017.05.002〉. 〈hal-01672877〉

Object Tracking by Hierarchical Decomposition of Hyperspectral Video Sequences: Application to Chemical Gas Plume Tracking

Guillaume Tochon, Jocelyn Chanussot, Mauro Dalla Mura, Andrea L. Bertozzi. Object Tracking by Hierarchical Decomposition of Hyperspectral Video Sequences: Application to Chemical Gas Plume Tracking. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2017, 55 (8), pp.4567 - 4585. 〈10.1109/TGRS.2017.2694159〉. 〈hal-01665299〉

Taking Optimal Advantage of Fine Spatial Resolution: Promoting partial image reconstruction for the morphological analysis of very-high-resolution images

Wenzhi Liao, Jocelyn Chanussot, Mauro Dalla Mura, Xin Huang, Rik Bellens, et al.. Taking Optimal Advantage of Fine Spatial Resolution: Promoting partial image reconstruction for the morphological analysis of very-high-resolution images. IEEE geoscience and remote sensing magazine, IEEE, 2017, 5 (2), pp.8 - 28. 〈10.1109/MGRS.2017.2663666〉. 〈hal-01665297〉

ENCADREMENT DE THESES / PhD THESIS SUPERVISED

Grenoble Images Parole Signal Automatique laboratoire

UMR 5216 CNRS - Grenoble INP - Université Joseph Fourier - Université Stendhal