Search results for " image processing."
showing 10 items of 2265 documents
Conjunction of Conditional Events and t-Norms
2019
We study the relationship between a notion of conjunction among conditional events, introduced in recent papers, and the notion of Frank t-norm. By examining different cases, in the setting of coherence, we show each time that the conjunction coincides with a suitable Frank t-norm. In particular, the conjunction may coincide with the Product t-norm, the Minimum t-norm, and Lukasiewicz t-norm. We show by a counterexample, that the prevision assessments obtained by Lukasiewicz t-norm may be not coherent. Then, we give some conditions of coherence when using Lukasiewicz t-norm
A Combined Fuzzy and Probabilistic Data Descriptor for Distributed CBIR
2009
With the wide diffusion of digital image acquisition devices, the cost of managing hundreds of digital images is quickly increasing. Currently, the main way to search digital image libraries is by keywords given by the user. However, users usually add ambiguos keywords for large set of images. A content-based system intended to automatically find a query image, or similar images, within the whole collection is needed. In our work we address the scenario where medical image collections, which nowadays are rapidly expanding in quantity and heterogeneity, are shared in a distributed system to support diagnostic and preventive medicine. Our goal is to produce an efficient content-based descript…
Scalable Clustering by Iterative Partitioning and Point Attractor Representation
2016
Clustering very large datasets while preserving cluster quality remains a challenging data-mining task to date. In this paper, we propose an effective scalable clustering algorithm for large datasets that builds upon the concept of synchronization. Inherited from the powerful concept of synchronization, the proposed algorithm, CIPA (Clustering by Iterative Partitioning and Point Attractor Representations), is capable of handling very large datasets by iteratively partitioning them into thousands of subsets and clustering each subset separately. Using dynamic clustering by synchronization, each subset is then represented by a set of point attractors and outliers. Finally, CIPA identifies the…
Weighted Fuzzy Clustering for Online Detection of Application DDoS Attacks in Encrypted Network Traffic
2016
Distributed denial-of-service (DDoS) attacks are one of the most serious threats to today’s high-speed networks. These attacks can quickly incapacitate a targeted business, costing victims millions of dollars in lost revenue and productivity. In this paper, we present a novel method which allows us to timely detect application-layer DDoS attacks that utilize encrypted protocols by applying an anomaly-based approach to statistics extracted from network packets. The method involves construction of a model of normal user behavior with the help of weighted fuzzy clustering. The construction algorithm is self-adaptive and allows one to update the model every time when a new portion of network tr…
Comparison of Internal Clustering Validation Indices for Prototype-Based Clustering
2017
Clustering is an unsupervised machine learning and pattern recognition method. In general, in addition to revealing hidden groups of similar observations and clusters, their number needs to be determined. Internal clustering validation indices estimate this number without any external information. The purpose of this article is to evaluate, empirically, characteristics of a representative set of internal clustering validation indices with many datasets. The prototype-based clustering framework includes multiple, classical and robust, statistical estimates of cluster location so that the overall setting of the paper is novel. General observations on the quality of validation indices and on t…
Fuzzy fixed points of generalized F2-geraghty type fuzzy mappings and complementary results
2016
The aim of this paper is to introduce generalized F2-Geraghty type fuzzy mappings on a metric space for establishing the existence of fuzzy fixed points of such mappings. As an application of our result, we obtain the existence of common fuzzy fixed point for a generalized F2-Geraghty type fuzzy hybrid pair. These results unify, generalize and complement various known comparable results in the literature. An example and an application to theoretical computer science are presented to support the theory proved herein. Also, to suggest further research on fuzzy mappings, a Feng–Liu type theorem is proved.
A heuristic fuzzy algorithm for assessing and managing tourism sustainability
2019
“Smartness” and “sustainability” are gaining growing attention from both practitioners and policy makers. “Smartness” and “sustainability” assessments are of crucial importance for directing, in a systemic perspective, the decision-making process toward sustainability and smart growth objectives. Sustainability assessment is a major challenge due to the multidisciplinary aspects involved that make the evaluation process complex and hinder the effectiveness of available monitoring tools. To achieve the assessment objective, we introduce an enhanced fuzzy logic-based framework for handling the inherent uncertainty and vagueness of the involved variables: we apply our approach to Italy, and we…
Novel threat-based AI strategies that incorporate adaptive data structures for multi-player board games
2016
This paper considers the problem of designing novel techniques for multi-player game playing, in a range of board games and configurations. Compared to the well-known case of two-player game playing, multi-player game playing is a more complex problem with unique requirements. To address the unique challenges of this domain, we examine the potential of employing techniques inspired by Adaptive Data Structures (ADSs) to rank opponents based on their relative threats, and using this information to achieve gains in move ordering and tree pruning. We name our new technique the Threat-ADS heuristic. We examine the Threat-ADS’ performance within a range of game models, employing a number of diffe…
On Addressing the Challenges of Complex Stochastic Games Using “Representative” Moves
2018
The problem of achieving competitive game play in a board game, against an intelligent opponent, is a well-known and studied field of Artificial Intelligence (AI). This area of research has seen major breakthroughs in recent years, particularly in the game of Go. However, popular hobby board games, and particularly Trading Card Games, have unique qualities that make them very challenging to existing game playing techniques, partly due to enormous branching factors. This remains a largely unexamined domain and is the arena we operate in. To attempt to tackle some of these daunting requirements, we introduce the novel concept of “Representative” Moves (RMs). Rather than examine the complete l…
Reduced reference 3D mesh quality assessment based on statistical models
2015
International audience; During their geometry processing and transmission 3D meshes are subject to various visual processing operations like compression, watermarking, remeshing, noise addition and so forth. In this context it is indispensable to evaluate the quality of the distorted mesh, we talk here about the mesh visual quality (MVQ) assessment. Several works have tried to evaluate the MVQ using simple geometric measures, However this metrics do not correlate well with the subjective score since they fail to reflect the perceived quality. In this paper we propose a new objective metric to evaluate the visual quality between a mesh with a perfect quality called reference mesh and its dis…