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DISTRIBUTED DATA WITH INCREMENTAL DETECTION OF INCONSISTENCIES

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Errors in the data are typically detected as violations of constraints (data quality rules), such as functional dependencies (FDs), denial constraints, and conditional functional dependencies (CFDs). When the data is in a centralized database, it is known that two SQL queries suffice to detect its violations of a set of CFDs. This abstract investigates incremental […]

IMAGE SEGMENTATION USING ITERATIVE TRICLASS THRESHOLDING TECHNIQUE

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In image processing, segmentation is often the first step to pre-process images to extract objects of interest for further analysis. We present a new method in image segmentation that is based on Otsu’s method but iteratively searches for sub regions of the image for segmentation, instead of treating the full image as a whole region […]

INCREMENTAL DETECTION IN DISTRIBUTED DATA

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Real life data is often dirty. To clean the data, efficient algorithms for detecting errors have to be in place. Errors in the data are typically detected as violations of constraints (data quality rules), such as functional dependencies (FDs), denial constraints, and conditional functional dependencies (CFDs). When the data is in a centralized database, it […]

SALIENCY DRIVEN NONLINEAR DIFFUSION FILTERING BASED IMAGE CLASSIFICATION USING MULTISCALE INFORMATION FUSION

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Image classification is perhaps the most important part of digital image analysis. It is very nice to have a “pretty picture” or an image, showing a magnitude of colors illustrating various features of the underlying terrain, but it is quite useless unless to know what the colors mean. The image is classified using multiscale information […]

SALIENCY DRIVEN IMAGE MULTISCALE NONLINEAR DIFFUSION FILTERING

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The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford […]

SPARSE BAYESIAN REGRESSION BASED PHOTOMETRIC STEREO FOR GENERAL DIFFUSE SURFACES

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            Photometric stereo involves estimating the surface normals of an object given appearance variations in multiple images taken under different lighting conditions. Most conventional algorithms for non-Lambertian photometric stereo can be partitioned into two categories. The first category is built upon stable outlier rejection techniques while assuming a dense Lambertian structure for the inliers, and […]

SPARSE BAYESIAN REGRESSION BASED PHOTOMETRIC STEREO FOR GENERAL DIFFUSE SURFACES

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Photometric stereo involves estimating the surface normals of an object given appearance variations in multiple images taken under different lighting conditions. Most conventional algorithms for non-Lambertian photometric stereo can be partitioned into two categories. The first category is built upon stable outlier rejection techniques while assuming a dense Lambertian structure for the inliers, and thus […]

FDM ALGORITHM BASED SECURE MINING OF ASSOCIATION RULES IN HORIZONTALLY DISTRIBUTED DATABASES

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Our protocol, like theirs, is based on the Fast Distributed Mining (FDM) algorithm of Cheung et al., which is an unsecured distributed version of the Apriori algorithm. The main ingredients in our protocol each of the interacting players hold, and another that tests the inclusion of an element held by one player in a subset […]

HORIZONTALLY DISTRIBUTED DATABASES USING SECURE MINING OF ASSOCIATION RULE

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There are several sites (or players) that hold homogeneous databases, i.e., databases that share the same schema but hold information on different entities. The goal is to find all association rules with support at least s and confidence at least c , for some given minimal support size s and confidence level c , that […]

PHOTOMETRIC STEREO FOR GENERAL DIFFUSE SURFACES USING SPARSE BAYESIAN REGRESSION

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Photometric stereo algorithm used for stably and accurately estimating the surface normals of a scene in the presence of various non-Lambertian effects. Most conventional algorithms for non-Lambertian photometric stereo can be partitioned into two categories. The first category is built upon stable outlier rejection techniques while assuming a dense Lambertian structure for the inliers, and […]