Today cartoon images take more portion of digital multimedia than ever as we notice this phenomenon in the entertainment business. With the explosive proliferation of cartoon image contents on the Internet, we seem to...
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In this paper, we present image genre classification system, called IGC. The proposed system categorizes images into one of three genres, such as art, photo, or cartoon images. The images features are extracted using ...
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We propose a method to extract salient contour groups from cluttered regions using Markov Random Fields. Our technique delineates smooth, long, and elliptical curves out of clutter. To extract salient curves, we use t...
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We propose a method to extract salient contour groups from cluttered regions using Markov Random Fields. Our technique delineates smooth, long, and elliptical curves out of clutter. To extract salient curves, we use the following perceptual rules: smoothness, proximity, co-circularity, co-elliptic, and length. Our method consists of the following steps: obtaining individual smooth contours along their saliency measures; starting from the most salient contour search for possible grouping options for each contour; continuing the grouping until an optimum solution is reached. We introduce circularity and saliency measures for open curves. We applied our method to discern coronal loops from cluttered solar images, and were able to successfully obtain the entire set of desired coronal loops while eliminating any cluttered background.
Urban Health(UH) leading organizations are confronting with complex and multi-domain problemsIntegration of knowledge and innovation strategies is to optimize resource, time and cost intensive processesThis paper disc...
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Urban Health(UH) leading organizations are confronting with complex and multi-domain problemsIntegration of knowledge and innovation strategies is to optimize resource, time and cost intensive processesThis paper discusses knowledge Management(KM) and Innovation Management(IM) concepts for exploration and exploitation of new idea or existing knowledge for supplying UH policy makersSocial and knowledge processes as KM tools feed up exploitation for existing knowledge and exploration for new idea on the basis of IM strategyThese are inputs of Radical-, Incremental-, Radar(RIR) strategies which are designed to effectively control or monitor the current situationRIR strategies are defined based on five identified situations(5S) that are determined through indication of three-color codes in Urban HEART MatrixThe proposed concept is consequently applying an analytical method for indication of transition and riskiness situationsThese strategies are supporting UH policy makers to identify improvement potentials based on acquired evidences, and to select and apply relevant strategy.
Telemedicine is a very important area in medical field that is expanding daily motivated by many researchers interested in improving medical applications. In Brazil was started in 2005, in the State of Santa Catarina ...
Telemedicine is a very important area in medical field that is expanding daily motivated by many researchers interested in improving medical applications. In Brazil was started in 2005, in the State of Santa Catarina has a developed server called the CyclopsDCMServer, which the purpose to embrace the HDF for the manipulation of medical images (DICOM) using a distributed file system. Since then, many researches were initiated in order to seek better performance. Our approach for this server represents an additional parallel implementation in I/O operations since HDF version 5 has an essential feature for our work which supports parallel I/O, based upon the MPI paradigm. Early experiments using four parallel nodes, provide good performance when compare to the serial HDF implemented in the CyclopsDCMServer.
In recent years, large amounts of uncertain data are emerged with the widespread employment of the new technologies, such as wireless sensor networks, RFID and privacy protection. According to the features of the unce...
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As the rapid growth of the scientific documents in digital libraries, the search demands for the documents as well as specific components increase dramatically. Accurately detecting the component boundary is of vital ...
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The current GPM algorithm needs many iterations to get good process models with high fitness which makes the GPM algorithm usually time-consuming and sometimes the result can not be accepted. To mine higher quality mo...
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In this paper we establish a framework for the convergence of two algorithms for solving the Nearest Point Problem in Reduced Convex Hulls (RCH-NPP), namely the RCH-GSK method proposed in [1] and the RCH-MDM method su...
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In this paper we establish a framework for the convergence of two algorithms for solving the Nearest Point Problem in Reduced Convex Hulls (RCH-NPP), namely the RCH-GSK method proposed in [1] and the RCH-MDM method suggested in [2]. This framework allows us to show the asymptotic convergence of both methods in a very simple way. Moreover, it allows to justify a shrinking strategy for RCH-MDM.
Collaborative filtering relies on numerical ratings for recommendations. While users consider various aspects of content as a basis of their evaluation, a numeric rating provides only an aggregated report of final ass...
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Collaborative filtering relies on numerical ratings for recommendations. While users consider various aspects of content as a basis of their evaluation, a numeric rating provides only an aggregated report of final assessment. The performance of a collaborative recommender system could be enhanced if the ratings are augmented by more specific information used for evaluation. In this paper, we present MovieCommenter, a recommender system that utilizes movie aspects - key features and users' opinions about the movie. We conducted a series of experiments to perform both qualitative and quantitative evauations of the system performance. The results show that our approach makes more precise recommendations than traditional approaches. Moreover, the interface of MovieCommenter was found to enhance the recommendation explanability, ability to explain how the recommendation was made. Because our approach is based on independent schema, this approach could be easily applied for recommending other domain contents.
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