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About 10,000 papers for “Structural pattern”

Structural Pattern Analysis

Roger Mohr, Th Pavlidis, Alberto Sanfeliu · WORLD SCIENTIFIC eBooks · 1990

Structural Pattern Analysis. Volume 19 of World Scientific Series in Computer Science. World Scientific, 1990.

Cited by 31

Structural Pattern Analysis

Sanfeliu, Alberto, Mohr, Roger, Pavlidis, Theo · DIGITAL.CSIC (Spanish National Research Council (CSIC)) · 2010

Structural Pattern Analysis. Volume 19 of World Scientific Series in Computer Science. World Scientific, 1990.

Cited by 0

Structural-Pattern Databases

Michael Katz, Carmel Domshlak · Proceedings of the International Conference on Automated Planning and Scheduling · 2009

Explicit abstraction heuristics, notably pattern-database and merge-and-shrink heuristics, are employed by some state-of-the-art optimal heuristic-search planners. The major limitation of these abstraction heuristics is that the size of the abstract space has to be bounded by a (large) constant. Targeting this issue, Katz and Domshlak (2008b) introduced structural, and in particular fork-decomposition, abstractions, in which the planning task is abstracted by an instance of a tractable fragment of optimal planning. At first view, however, the lunch was not free. Some of the power of the explicit abstraction heuristics comes from pre-computing the heuristic function offline, and then determine h(s) for each evaluated state s by a very fast lookup in a "database." In contrast, fork-decomposition offer a poly-time, yet far from being fast, computation. In this contribution, we show that the time-per-node complexity bottleneck of the fork-decomposition heuristics can be successfully overcome. Specifically, we show that an equivalent of the explicit abstractions' notion of "database" exists for the fork-decomposition abstractions as well, and this despite of their exponential-size abstract spaces. Experimentally, we show that heuristic search with such "databased" fork-decomposition heuristics favorably competes with the state-of-the-art of optimal planning.

Cited by 12Open access

Structural pattern analysis

Mohr, Roger, Pavlidis, Theodosios, Sanfeliu, Alberto

This book contains a selection of 14 papers presented at the workshop organised by the International Association for Pattern Recognition (IAPR) Technical Committee on Syntactical and Structural Pattern Recognition, at Pont-à-Mousson, 1988. These papers which have been expanded, focus on both fundamental aspects and applications. They show that structural methods are a good framework for integrating both symbolic and numerical knowledge for modeling, recognition and also learning. The applications described are on document analysis, speech and image analysis

Cited by 0

Orientation Selectivity Structural Pattern

Jinjian Wu, Weisi Lin, Guangming Shi et al. · Code Ocean · 2017

Visual Orientation Selectivity based Structure Description, Version 1.0 Copyright(c) 2015 Jinjian Wu, Weisi Lin, and Guangming Shi All Rights Reserved. This is an implementation of the algorithm for creating the orientation selectivity based structure descriptor. Please refer to the following papers Jinjian Wu, Weisi Lin, Guangming Shi, Yazhong Zhang, Weisheng Dong, Zhibo Chen "Visual Orientation Selectivity based Structure Description", IEEE Trans. On Image Processing, Vol. 24, No. 11, PP. 4602-4613, Nov. 2015.

Cited by 0Open access

Structural Pattern Matching - Succinctly

Arnab Ganguly, Rahul Shah, Sharma V. Thankachan · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · 2017

Let T be a text of length n containing characters from an alphabet \Sigma, which is the union of two disjoint sets: \Sigma_s containing static characters (s-characters) and \Sigma_p containing parameterized characters (p-characters). Each character in \Sigma_p has an associated complementary character from \Sigma_p. A pattern P (also over \Sigma) matches an equal-length substring $S$ of T iff the s-characters match exactly, there exists a one-to-one function that renames the p-characters in S to the p-characters in P, and if a p-character x is renamed to another p-character y then the complement of x is renamed to the complement of y. The task is to find the starting positions (occurrences) of all such substrings S. Previous indexing solution [Shibuya, SWAT 2000], known as Structural Suffix Tree, requires \Theta(n\log n) bits of space, and can find all occ occurrences in time O(|P|\log \sigma+ occ), where \sigma = |\Sigma|. In this paper, we present the first succinct index for this problem, which occupies n \log \sigma + O(n) bits and offers O(|P|\log\sigma+ occ\cdot \log n \log\sigma) query time.

Cited by 3Open access

for Structural Pattern Recognition

In Time-Series Data, Robert T. Olszewski, Christos Faloutsos et al. · 2001

Pattern recognition encompasses two fundamental tasks: description and classification. Given an object to analyze, a pattern recognition system first generates a description of it (i.e., the pattern) and then classifies the object based on that description (i.e., the recognition). Two general approaches for implementing pattern recognition systems, statistical and structural, employ different techniques for description and classification. Statistical approaches to pattern recognition use decision-theoretic concepts to discriminate among objects belonging to different groups based upon their quantitative features. Structural approaches to pattern recognition use syntactic grammars to discriminate among objects belonging to different groups based upon the arrangement of their morphological (i.e., shape-based or structural) features. Hybrid approaches to pattern recognition combine aspects of both statistical and structural pattern recognition.

Cited by 0

Structural correlation pattern mining . . .

Arlei Silva, Wagner Meira, Jr., Mohammed J. Zaki · 2010

In this paper we define the Structural Correlation Pattern (SCP) mining problem, which consists of determining correlations among vertex attributes and dense components in an undirected graph. Vertex attributes play an important role in several real-life graphs and SCPs help to understand how they relate to the associated graph topology. SCPs may describe, for example, interesting relationships between personal characteristics and the community structure in social networks. We also propose an efficient algorithm, called SCORP, to extract SCPs from large graphs, and compare it against a naive approach for SCP mining, demonstrating its scalability and efficiency. We also discuss the application of SCORP to two actual scenarios, co-authorship networks and social music discovery, showing relevant results that demonstrate the applicability of the proposed approach.

Cited by 0

Graph-Based Structural Pattern Learning

Lawrence B. Holder, Diane J. Cook · 2006

Abstract : The main objective of this project was to design, implement and evaluate new methods for performing pattern learning on structured data represented as graphs and evaluate their application to structural, relational databases relevant to the Evidence Assessment, Grouping, Linking and Evaluation (EAGLE) program. This work builds on existing methods for graph-based knowledge discovery and concept learning implemented in the SUBDUE structural pattern learning system. The graph-based structural pattern learning algorithm was extended to perform structural concept learning and structural, hierarchical conceptual clustering. The resulting system was evaluated using several structural databases, including those with known structural patterns, those of relevance to the target domains of the EAGLE program, and those developed as challenge problems within the EAGLE program.

Cited by 0

Structural pattern and neotectonic activity

ivkoviæ Peria, Èupkoviæ Tomas, Pavloviæ Radmila et al. · SHILAP Revista de lepidopterología · 1996

The north-eastern Serbia is one of the most important ore bearing areas in Yugoslavia and Balkan. The Bor and Majdanpek are world-wide known copper ore deposits. Mineralization is con-nected with the Upper Cretaceous magmatism. The main ore controlling factor is fracture pattern. The investigations of structural and morphological characteristics carried out in the wider Majdan-pek area supplied new data on disjunctive structures and indicated an intensive neotectonic activity. A high degree of correspondence between the older fracture pattern and neotectonically active rup-tures has been discovered. Tectonic activity that produced the Upper Cretaceous magmatism was prolonged through the Tertiary and Quaternary. The older ruptures were neotectonically reactivated, changing many times the sense and intensity of vertical movements. The obtained results are a reliable base for selection of perspective ore bearing areas and ra-tional planning of further detailed field structural and metallogenic investigations.

Cited by 0Open access

Structural Pattern Drills: A Classification

Christina Bratt Paulston · Foreign Language Annals · 1970

ABSTRACT This article attempts a reclassification of structural pattern drills, taking into account the theories of Skinner as well as Chomsky on language learning. Structural pattern drills are classified into mechanical, meaningful, and communicative drills and analyzed in terms of (1) expected terminal behavior, (2) response control, (3) the type of learning process involved, and (4) utterance response. The author believes that if there is more than one level of language and more than one type of learning, this should be reflected in the nature and use of drills in order to provide a systematic and more efficient progression in the classroom learning of foreign languages from mechanical learning to the internalizing of competence.

Cited by 54

Hierarchies in structural pattern recognition

T. Pavlidis · Proceedings of the IEEE · 1979

This paper discusses a hierarchical approach to pattern analysis and recognition. A general discussion of the labeling problem in structural pattern recognition is followed by a discussion of a specific technique for shape analysis. The number of levels in the hierarchy depends on the complexity of the scene, and, with the exemption of the first two levels, the processing is of standard syntactical form.

Cited by 29