Searching for authors named "George Tzagkarakis" – sorted by Relevance.
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A statistical approach to texture image retrieval via alpha-stable modeling of wavelet decompositions
- This paper addresses issues that arise in content-based information retrieval systems, which employ statistical feature extraction and similarity measurements of texture images. First, we observe that statistical distributions with heavy algebraic tails, such as the alpha-stable family, are in many
- Cited by 6 (6 self) – Add To MetaCart
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Rotation-invariant texture retrieval with Gaussianized steerable pyramids
- Abstract—This paper presents a novel rotation-invariant image retrieval scheme based on a transformation of the texture information via a steerable pyramid. First, we fit the distribution of the subband coefficients using a joint alpha-stable sub-Gaussian model to capture their non-Gaussian behavior
- Cited by 5 (3 self) – Add To MetaCart
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Singular Spectrum Analysis of Traffic Workload in a Large-Scale Wireless LAN ∗ ABSTRACT
- Network traffic load in an IEEE802.11 infrastructure arises from the superposition of traffic accessed by wireless clients associated with access points (APs). An accurate characterization of these data can be beneficial in modelling network traffic and addressing a variety of problems including cov
- Cited by 1 (1 self) – Add To MetaCart
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Trend forecasting based on Singular Spectrum Analysis of traffic
- journal homepage: www.elsevier.com/locate/peva
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On a Probabilistic Combination of Prediction Sources
- Abstract. Recommender Systems (RS) are applications that provide personalized advice to users about products or services they might be interested in. To improve recommendation quality, many hybridization techniques have been proposed. Among all hybrids, the weighted recommenders have the main benefi
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2 ”Group of Information and Communication Systems”
- This paper addresses the construction of a novel efficient rotation-invariant texture retrieval method that is based on the alignment in angle of signatures obtained via a steerable sub-Gaussian model. In our proposed scheme, we first construct a steerable multivariate sub-Gaussian model, where the
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