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Sarhrouni E.,LRIT | Hammouch A.,Mohammed V University | Aboutajdine D.,LRIT
2nd International Conference on Innovative Computing Technology, INTECH 2012 | Year: 2012

Hyperspectral images (HSI) classification is a high technical remote sensing tool. The main goal is to classify the point of a region. The HIS contains more than a hundred bidirectional measures, called bands (or simply images), of the same region called Ground Truth Map (GT). Unfortunately, some bands contain redundant information, others are affected by the noise, and the high dimensionalities of features make the accuracy of classification lower. All these bands can be important for some applications, but for the classification a small subset of these is relevant. In this paper we use mutual information (MI) to select the relevant bands; and the Normalized Mutual Information coefficient to avoid and control redundant ones. This is a feature selection scheme and a Filter strategy. We establish this study on HSI AVIRIS 92AV3C. This is effectiveness, and fast scheme to control redundancy. © 2012 IEEE. Source


Sarhrouni E.,LRIT | Hammouch A.,Mohammed V University | Aboutajdine D.,LRIT
International Journal of Tomography and Simulation | Year: 2014

In the feature classification domain, the choice of data affects widely the results. The Hyperspectral image (HSI), is a set of more than a hundred bidirectional measures (called bands), of the same region (called ground truth map: GT). The HSI is modelized at a set of N vectors. So we have N features (or attributes) expressing N vectors of measures for C substances (called classes). The problematic is that it's pratically impossible to investgate all possible subsets. So we must find K vectors among N, such as relevant and no redundant ones; in order to classify substances. Here we introduce an algorithm based on Normalized Mutual Information to select relevant and no redundant bands, necessary to increase classification accuracy of HSI. © 2014 by CESER PUBLICATIONS. Source


Sarhrouni E.,LRIT | Hammouch A.,LRIT | Hammouch A.,Mohammed V University | Aboutajdine D.,LRIT
Proceedings of 2012 International Conference on Multimedia Computing and Systems, ICMCS 2012 | Year: 2012

Hyperspectral image is a substitution of more than a hundred images, called bands, of the same region. They are taken at juxtaposed frequencies. The reference image of the region is called Ground Truth map (GT). the problematic is how to find the good bands to classify the pixels of regions; because the bands can be not only redundant, but a source of confusion, and decreasing so the accuracy of classification. Some methods use Mutual Information (MI) and threshold, to select relevant bands. Recently theres an algorithm selection based on mutual information, using bandwidth rejection and a threshold to control and eliminate redundancy. The band top ranking the MI is selected, and if its neighbors have sensibly the same MI with the GT, they will be considered redundant and so discarded. This is the most inconvenient of this method, because this avoids the advantage of hyperspectral images:: some precious information can be discarded. In this paper well make difference between useful and useless redundancy. A band contains useful redundancy if it contributes to decreasing error probability. According to this scheme, we introduce new algorithm using also mutual information, but it retains only the bands minimizing the error probability of classification. To control redundancy, we introduce a complementary threshold. So the good band candidate must contribute to decrease the last error probability augmented by the threshold. This process is a wrapper strategy; it gets high performance of classification accuracy but it is expensive than filter strategy. © 2012 IEEE. Source


Moretto A.,LRIT | Colin E.,LRIT | Ripoll C.,ESYCOM | Abou Chakra S.,Harriri Canadian University
Proceedings of the IEEE | Year: 2010

This paper deals with ultra-high-frequency (UHF) radio-frequency identification (RFID) tag modeling. Examples of electrical models and measurements of backscattering by load modulation in RFID systems can be found in scientific literature in far-field conditions. Load modulation and loading effect are based on the same physical phenomenon: the antenna current is modified by switching the load impedance between two impedances which are frequency dependent. All these models neglect the shunt resistance which can deeply affect the load impedance and may produce failures in the communication system. © 2006 IEEE. Source


Miraoui A.,CNRS Risk Management Science and Technology | Mabrouk K.,LRIT | Snoussi H.,CNRS Risk Management Science and Technology | Amerhaye A.,LRIT | Duchene J.,CNRS Risk Management Science and Technology
7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011 | Year: 2011

The aim of this work is dedicated to creating smart environments and assistance to enable elderly to live a longer and more independent life at home. One of the essential services required to maximize the intelligence of a smart environment is a low cost indoor precision localization system. This paper presents our hands-on experience based on our first phase work to build up a smart home infrastructure for the elderly. We review location tracking technology and describe the rationale behind our choice among the emerging wireless sensors technologies. Node localization is required to report the origin of events, to assist group querying of sensors, to facilitate routing and to answer questions on the network coverage. Furthermore, one of the fundamental challenges in a wireless sensor network is mobile node localization. In this work, we locate in real-time a person in an indoor environment rich in multipaths by taking into account the effects of the environment. Future research directions and challenges for improving node localization in wireless sensor networks are also discussed. © 2011 IEEE. Source

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