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pro vyhledávání: '"Tourneret, Jean‐Yves"'
Autor:
Haouari, Jihanne El, Gaucel, Jean-Michel, Pittet, Christelle, Tourneret, Jean-Yves, Wendt, Herwig
Accurate estimates of Instrument Spectral Response Functions (ISRFs) are crucial in order to have a good characterization of high resolution spectrometers. Spectrometers are composed of different optical elements that can induce errors in the measure
Externí odkaz:
http://arxiv.org/abs/2404.05298
Hyperbolic geometry has recently garnered considerable attention in machine learning due to its capacity to embed hierarchical graph structures with low distortions for further downstream processing. This paper introduces a simple framework to detect
Externí odkaz:
http://arxiv.org/abs/2312.03895
Publikováno v:
IEEE Transactions on Signal Processing, vol. 71, pp. 1669-1682, 2023
This paper tackles the problem of missing data imputation for noisy and non-Gaussian data. A classical imputation method, the Expectation Maximization (EM) algorithm for Gaussian mixture models, has shown interesting properties when compared to other
Externí odkaz:
http://arxiv.org/abs/2201.12020
Autor:
Mouret, Florian, Albughdadi, Mohanad, Duthoit, Sylvie, Kouamé, Denis, Rieu, Guillaume, Tourneret, Jean-Yves
Missing data is a recurrent problem in remote sensing, mainly due to cloud coverage for multispectral images and acquisition problems. This can be a critical issue for crop monitoring, especially for applications relying on machine learning technique
Externí odkaz:
http://arxiv.org/abs/2110.11780
Autor:
Mouret, Florian, Albughdadi, Mohanad, Duthoit, Sylvie, Kouamé, Denis, Rieu, Guillaume, Tourneret, Jean-Yves
Publikováno v:
Remote Sens. 2021, 13(5), 956
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 rapeseed and wheat parcels located in Beauce (France). The proposed m
Externí odkaz:
http://arxiv.org/abs/2004.08431
Autor:
Rapp, Joshua, Saunders, Charles, Tachella, Julián, Murray-Bruce, John, Altmann, Yoann, Tourneret, Jean-Yves, McLaughlin, Stephen, Dawson, Robin M. A., Wong, Franco N. C., Goyal, Vivek K
Non-line-of-sight (NLOS) imaging is a rapidly growing field seeking to form images of objects outside the field of view, with potential applications in search and rescue, reconnaissance, and even medical imaging. The critical challenge of NLOS imagin
Externí odkaz:
http://arxiv.org/abs/2002.07118
Autor:
Borsoi, Ricardo Augusto, Imbiriba, Tales, Bermudez, José Carlos Moreira, Richard, Cédric, Chanussot, Jocelyn, Drumetz, Lucas, Tourneret, Jean-Yves, Zare, Alina, Jutten, Christian
The spectral signatures of the materials contained in hyperspectral images, also called endmembers (EM), can be significantly affected by variations in atmospheric, illumination or environmental conditions typically occurring within an image. Traditi
Externí odkaz:
http://arxiv.org/abs/2001.07307
Akademický článek
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Autor:
Tachella, Julián, Altmann, Yoann, Mellado, Nicolas, McCarthy, Aongus, Tobin, Rachael, Buller, Gerald S., Tourneret, Jean-Yves, McLaughlin, Stephen
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 time required for the analysis of the recorded data. Here we show a n
Externí odkaz:
http://arxiv.org/abs/1905.06700
Autor:
Tachella, Julián, Altmann, Yoann, Márquez, Miguel, Arguello-Fuentes, Henry, Tourneret, Jean-Yves, McLaughlin, Stephen
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 range precision and low laser power. A multispectral single-photon Lidar s
Externí odkaz:
http://arxiv.org/abs/1904.02583