activity
20152020
most citedAn unsupervised bayesian approach for the joint reconstruction and classification of cutaneous reflectance confocal microscopy images

11 citations · 15 across the 4 of their papers we have counts for

collaborators

11 papers

eess.IV2020

Outlier detection at the parcel-level in wheat and rapeseed crops using multispectral and SAR time series

Florian Mouret, Mohanad Albughdadi, Sylvie Duthoit +3

This paper studies the detection of anomalous crop development at the parcel-level based on an unsupervised outlier detection technique. The experimental validation is conducted on…

eess.IV2020

Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review

Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez +6

The spectral signatures of the materials contained in hyperspectral images, also called endmembers (EM), can be significantly affected by variations in atmospheric, illumination or…

eess.IV2019

Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers

Julián Tachella, Yoann Altmann, Nicolas Mellado +5

Single-photon lidar has emerged as a prime candidate technology for depth imaging through challenging environments. Until now, a major limitation has been the significant amount of…

eess.SP2019

Bayesian 3D Reconstruction of Subsampled Multispectral Single-photon Lidar Signals

Julián Tachella, Yoann Altmann, Miguel Márquez +3

Light detection and ranging (Lidar) single-photon devices capture range and intensity information from a 3D scene. This modality enables long range 3D reconstruction with high rang…

eess.IV2019

Preconditioned P-ULA for Joint Deconvolution-Segmentation of Ultrasound Images -- Extended Version

Corbineau Marie-Caroline, Kouamé Denis, Chouzenoux Emilie +2

Joint deconvolution and segmentation of ultrasound images is a challenging problem in medical imaging. By adopting a hierarchical Bayesian model, we propose an accelerated Markov c…

eess.IV2018

Bayesian 3D Reconstruction of Complex Scenes from Single-Photon Lidar Data

Julián Tachella, Yoann Altmann, Ximing Ren +4

Light detection and ranging (Lidar) data can be used to capture the depth and intensity profile of a 3D scene. This modality relies on constructing, for each pixel, a histogram of…