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Speckle removal from single-channel and multi-dimensional SAR remains a difficult problem. In this paper, we are investigating the use of a Convolutional Neural Network (CNN), previously applied to the Super-Resolution problem, for speckle removal. Because speckle noise statistics is signal dependent, we are training the neural network on the residual image formed by the ratio of the observed intensity...
Extracting and identifying objects in very high resolution imagery has been a popular research topic in remote sensing. Since the beginning of this decade, deep learning techniques have revolutionized computer vision providing significant performance gains compared to traditional “shallow” techniques in various challenging vision problems. The training of deep neural networks usually requires very...
Hybrid systems of energy production are considered as an interesting alternative for power supply of remote area and non connected sites. Indeed, this paper is focused on the design of an intelligent algorithm and optimized strategy for power management of a renewable hybrid system. This system which includes wind generator (WG), photovoltaic panel (PV), battery storage (BS) and diesel engine (DE)...
This paper proposes an intelligent algorithm for optimal management power applied to hybrid renewable standalone system. This hybrid system focuses on the combination of wind turbine (WT), photovoltaic (PV) as the main sources of energy and storage batteries, in addition, it uses and diesel engine as an additional source of rescue and dump load to dissipate thee overproduction when there is. The load...
This paper proposes new method of monitoring and fault detection in photovoltaic systems, based mainly on the analysis of the power losses of the photovoltaic system (PV) by using statistical signal processing. Firstly, real time new universal circuit based model of photovoltaic panels is presented. Then, the development of software fault detection on a real installation is performed under the MATLAB/Simulink...
A photovoltaic (PV) conversion system consisting of PV Panel, DC/DC boost converter and a DC (Direct Current) load, is considered in this work. This paper proposes T-S fuzzy method to deal with Maximum Power Point Tracking (MPPT) problem. The stability analysis of the closed loop system is carried out using Lyapunov method and the control gains can be designed by solving Linear Matrix Inequality (LMI)...
This research is presented a new algorithm and method for fault detection of photovoltaic panels in Residential Photovoltaic System (RPS). Our proposed PV performance diagnosis system is consist of two parts, passive and active part. In the passive diagnosis part, residue value is generated with Model Base Fault Diagnosis (MBFD) method to observe clear alarm signal from arbitrary data. As well, statistical...
This paper proposes an algorithm of maximum power point tracking (MPPT) applied for photovoltaic (PV) power generation systems. The strategy of this algorithm considers the value of short circuit current to generate the current at the maximum power. In this work, the current reference is generated by genetic algorithm (GA). In this way, short-circuit current measurements are not necessary, thus overcoming...
The aim of this study is to elaborate and validate a methodology to automatically assess head orientation with respect to a camera in a video sequence. The proposed method uses relatively stable facial features (upper points of the eyebrows, upper nasolabial-furrow corners and nasal root) that have symmetric properties to recover the face slant and tilt angles. These fiducial points are characterized...
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