18 résultats avec le mot-clé: 'smartphone sensors based indoor localization using neural networks'
Keywords: Indoor localization · magnetic field · smartphone sensors · deep neural net- works.. 1 Introduction
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Figure 5 shows the effect of the number of augmented data samples on the mean square error of the position estimation2.
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“Smartphone-based indoor localization system using inertial sensor and acoustic transmitter/receiver,” IEEE Sensors Journal, vol. Wang, “Toa estimation of chirp signal in
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This proposed approach is tested on a simulated environment, using a real propagation model based on measurements, and compared with the classi- cal matrix completion approach, based
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Zoning-based Localization in Indoor Sensor Networks Using Belief Functions Theory.. Daniel Alshamaa, Farah Mourad-Chehade,
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Orbites r´ eguli` eres et transition de phases hors-d’´ equilibre dans les syst` emes avec interactions ` a longue port´ eeR.
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L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des
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In this paper, we have proposed a novel approach to- wards automatic indoor human activity recognition, us- ing deep neural networks that take as input data orig- inating from radar
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Abstract— In this article, a new approach to the problem of indoor navigation based on ultrasonic sensors is presented, where artificial neural networks (ANN) are used to estimate
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1- Le contrat entre la Ville de Lyon / Orchestre national de Lyon et la société Askonas Holt Limited pour l’organisation de la tournée de l’Orchestre National de Lyon en Russie
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A hierarchical clustering technique is then applied to create a two-level hierarchy composed of clusters and of original zones in each cluster.. At each level of the hierarchy,
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L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des
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Final altitude zones are: Lowland Vegetation (1-2500m), Subparamo Vegetation (2501-3500), Paramo Vegetation (3501-4100) and Superparamo Vegetation (4101 – 5000).. These zones are
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The kernel density estimation was used to set mass functions, and the belief functions theory combined evidence to determine the sensor’s zone. Experiments on real data prove
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Human indoor localization is usually performed using Pyroelectric Infra- Red PIR sensors network, however, the latter presents several limitations, and to cope
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In this thesis, indoor localization is realized making use of received signal strength fingerprinting technique based on the existing GSM networks, which can be adopted by
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One “will then adapt” the last interval to fall down exactly on the end value ( JUSQU_A). It may be imprecise and inaccurate in whole or in part and is provided as
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