Active learning for efficient data selection in radio‐signal‐based positioning via deep learning

Autor: Vincent Corlay, Milan Courcoux‐Caro

Publikováno v: Electronics Letters, Vol 60, Iss 20, Pp n/a-n/a (2024)

Abstract The problem of user equipment positioning based on radio signals is considered via deep learning. As in most supervised‐learning tasks, a critical aspect is the availability of a relevant dataset to train a model. However, in a cellular ne

Externí odkaz: https://doaj.org/article/65b754fc86ae43eca8baeec24ffd797b

Sequential Sensor Placement using Bayesian Compressed Sensing for Source Localization

Autor: Alexandre Baussard, Charles Vanwynsberghe, Milan Courcoux-Caro, Cédric Herzet

Publikováno v: EUSIPCO 2020-28th European Signal Processing Conference
EUSIPCO 2020-28th European Signal Processing Conference, Jan 2021, Amsterdam, Netherlands. pp.241-245, ⟨10.23919/Eusipco47968.2020.9287709⟩
EUSIPCO

International audience; This paper deals with the sensor placement problem for an array designed for source localization. When it involves the identification of a few sources, the compressed sensing framework is known to find directions effectively t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49aea58314cd2aa9b4d47d09581ece3f
https://inria.hal.science/hal-03070390/document

Sequential sensor selection for the localization of acoustic sources by sparse Bayesian learninga).

Autor: Courcoux-Caro, Milan, Vanwynsberghe, Charles, Herzet, Cédric, Baussard, Alexandre

Publikováno v: Journal of the Acoustical Society of America; Sep2022, Vol. 152 Issue 3, p1695-1708, 14p