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In this paper, we present a quantitative analysis of the error in the reconstruction of a 3D scene which has been captured with Synthetic Aperture Integral Imaging system. The 3D information is obtained from 2D images for which the camera parameters are unknown. The model used for calibrating the Integral Imaging camera setup is based on fuzzy systems. These systems provide the opportunity for modeling...
Dams are very important economical and social structures that have a great impact on the population living in surrounding area. Dam surveillance is a complex process which involves data acquisition and analysis techniques, implying both measurements from sensors and transducers placed in the dam body and its surroundings, and also visual inspection. In order to enhance the visual inspection process...
Present energy problems involve issues of technology selection, placement, variation of energy services demand by location and time-of-use and new sourcing options especially renewable energy. Beside these issues, there are also, major challenges for current energy production where the cost and environmental impacts are some of the important aspects which determine the producers to consider alternative...
The monitoring and behavioral prediction of the hydrodams and hydrotechnical sites relies on the analysis of some objective information, the large number of sensors and examination modalities renders the human inspection of this information very difficult if not even impossible. The main objective of system is to provide a solution to overcome this problem through the development of a decision support...
Hydro-dams safety represents an important concern since their failure could be critical for the society. A key part of the hydro-dams surveillance programs is their visual inspection. However few computer vision support tools for implementing semi-automatically and objectively the visual surveillance and observation of the hydro-dams components exist. One of the issues addressed during the visual...
This paper proposes a classification scheme of prostate cancer patients based on support vector machines (SVM) classifiers that allow including the diagnosed prostate cancer patients into risk classes, before performing radical prostatectomy, according to their medical parameters. Our objective is to assess the use of SVM in order to predict the individual result of radical prostatectomy performed...
Underwater images analysis is a difficult task due to their specific attributes: weak and variable lighting, low contrast, blurring. Therefore powerful image analysis algorithms, application specific, must be employed to obtain good results. In this paper we propose such a novel architecture based on a support vector machine (SVM) classifier, dedicated to large underwater scenes analysis for the specific...
Support vector machines (SVMs) are powerful classifiers, with very good recognition rates in image analysis tasks. However their computational time in the object recognition phase is often large due to the number of classifications per scene and to the feature vector size, especially when the feature space is formed from raw image data. Several methods are reported in the literature to make the classification...
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