In this paper, we investigates the problem of planning and tracking trajectory for a non linear system which is the quadrotor using the flatness theory. The proposed flatness algorithm is real time implemented. The Ex...
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Radio Frequency IDentification (RFID) was identified as one of the ten best technologies in the 21st century. This technology is frequently used in different sectors: industrial, agricultural and academic. In RFID net...
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To reduce the power consumption, in the literature, most works have focused in the field of batteries. However despite the progress made in this area, it is difficult to increase the battery capacity without increasin...
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This work proposes an optimal trajectory generation and a controller design for a mobile robot. The objective consists of creating a new performance guidance module for the mobile robot in a closed environment. The re...
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作者：
Rahma KalboussiAymen AzazaMehrez AbdellaouiAli DouikENISO
Ecole Nationale d'Ingénieurs de Sousse NOCCS Networked Objects Control and Communication Systems Laboratory Soussel Tunisiay ENIM
Ecole Nationale d'Ingénieurs de Monastir NOCCS Laboratory Monastir Tunisia ENISO
NOCCS Laboratory Sousse Tunisia
In the last decades, saliency detection was extensively studied. The number of computational models that help to detect salient regions in still images is increasing, whereas, detecting salient regions in videos is in...
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In the last decades, saliency detection was extensively studied. The number of computational models that help to detect salient regions in still images is increasing, whereas, detecting salient regions in videos is in its early stages. In this paper we propose a video saliency detection method using local motion estimation. Starting from a patch, the problem of saliency detection is modeled as a growing region starting from a region which contains the higher motion information to the background. Local saliency is measured by combining local motion estimation and local surrounding contrast which leads to the construction of foreground and background patches. Experiments have proved that The proposed method outperforms state-of-the-art methods over two benchmark datasets.
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