the proceedings contain 26 papers. the topics discussed include: picture ID authentication using invisible watermark and facial recognition features;a new REF classifier for buried tag recognition;novel circular-shift...
ISBN:
(纸本)9728865287
the proceedings contain 26 papers. the topics discussed include: picture ID authentication using invisible watermark and facial recognition features;a new REF classifier for buried tag recognition;novel circular-shift invariant clustering;inductive string template-based learning of spoken language;a multi-resolution learning approach to tracking concept drift and recurrent concepts;automatic recognition of pollutants in packaged foods from x-ray imaging;car license plate extraction from video stream in complex environment;dynamic feature selection and coarse-to-fine search for content-based image retrieval;automated annotation of multimedia audio data with affective labels for information management;fast algorithm for optimal polygonal approximation of shape boundaries;activity identification and visualization;evaluating patternrecognition techniques in intrusion detection systems;and a comparison of methods for web document classification.
this book constitutes the refereed proceedings of the 12th IAPR-TC-15 internationalworkshop on graph-based Representation in patternrecognition, GbRPR 2019, held in Tours, France, in June 2019.;the 22 full...
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ISBN:
(数字)9783030200817
ISBN:
(纸本)9783030200800
this book constitutes the refereed proceedings of the 12th IAPR-TC-15 internationalworkshop on graph-based Representation in patternrecognition, GbRPR 2019, held in Tours, France, in June 2019.;the 22 full papers included in this volume together with an invited talk were carefully reviewed and selected from 28 submissions. the papers discuss research results and applications at the intersection of patternrecognition, image analysis, and graphtheory. they cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph embedding, spectral graph problems, and parallel algorithms for graph problems.
We introduce a method for computing homology groups and their generators of a 2D image, using a hierarchical structure i.e. irregular graph pyramid. Starting from an image, a hierarchy of the image is built, by two op...
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ISBN:
(纸本)9783540729020
We introduce a method for computing homology groups and their generators of a 2D image, using a hierarchical structure i.e. irregular graph pyramid. Starting from an image, a hierarchy of the image is built, by two operations that preserve homology of each region. Instead of computing homology generators in the base where the number of entities (cells) is large, we first reduce the number of cells by a graph pyramid. then homology generators are computed efficiently on the top level of the pyramid, since the number of cells is small, and a top down process is then used to deduce homology generators in any level of the pyramid, including the base level i.e. the initial image. We show that the new method produces valid homology generators and present some experimental results.
the traveling salesperson problem (TSP) is difficult to solve for input instances with large number of cities. Instead of finding the solution of an input with a large number of cities, the problem is approximated int...
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ISBN:
(纸本)9783540729020
the traveling salesperson problem (TSP) is difficult to solve for input instances with large number of cities. Instead of finding the solution of an input with a large number of cities, the problem is approximated into a simpler form containing smaller number of cities, which is then solved optimally. graph pyramid solution strategies, in a bottom-up manner using Boruvka's minimum spanning tree, convert a 2D Euclidean TSP problem with a large number of cities into successively smaller problems (graphs) with similar layout and solution, until the number of cities is small enough to seek the optimal solution. Expanding this tour solution in a top-down manner to the lower levels of the pyramid approximates the solution. the new model has an adaptive spatial structure and it simulates visual acuity and visual attention. the model solves the TSP problem sequentially, by moving attention from city to city withthe same quality as humans. graph pyramid data structures and processing strategies are a plausible model for finding near-optimal solutions for computationally hard patternrecognition problems.
We compare different statistical characterizations of a set of strings, for three different histogram-based distances. Given a distance, a set of strings may be characterized by its generalized median, i.e., the strin...
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ISBN:
(纸本)9783540729020
We compare different statistical characterizations of a set of strings, for three different histogram-based distances. Given a distance, a set of strings may be characterized by its generalized median, i.e., the string -over the set of all possible strings- that minimizes the sum of distances to every string of the set, or by its set median, i.e., the string of the set that minimizes the sum of distances to every other string of the set. For the first two histogram-based distances, we show that the generalized median string can be computed efficiently;for the third one, which biased histograms with individual substitution costs, we conjecture that this is a NP-hard problem, and we introduce two different heuristic algorithms for approximating it. We experimentally compare the relevance of the three histogram-based distances, and the different statistical characterizations of sets of strings, for classifying images that are represented by strings.
Reverse-convex programming (RCP) concerns global optimization of a specific class of non-convex optimization problems. We show that a recently proposed model for sparse non-negative matrix factorization (NMF) belongs ...
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ISBN:
(纸本)3540302875
Reverse-convex programming (RCP) concerns global optimization of a specific class of non-convex optimization problems. We show that a recently proposed model for sparse non-negative matrix factorization (NMF) belongs to this class. based on this result, we design two algorithms for sparse NMF that solve sequences of convex secondorder cone programs (SOCP). We work out some well-defined modifications of NMF that leave the original model invariant from the optimization viewpoint. they considerably generalize the sparse NMF setting to account for uncertainty in sparseness, for supervised learning, and, by dropping the non-negativity constraint, for sparsity-controlled PCA.
We propose a new fast algorithm for solving the Maximum Common Subgraph (MCS) problem. MCS is an NP-complete problem. In this paper, we focus on a special class of graphs, i.e. Planar Triangulation graphs, which are c...
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this book constitutes the refereed proceedings of the 11th IAPR-TC-15 internationalworkshop on graph-based Representation in patternrecognition, GbRPR 2017, held in Anacapri, Italy, in May 2017. the 25 full papers a...
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ISBN:
(数字)9783319589619
ISBN:
(纸本)9783319589602
this book constitutes the refereed proceedings of the 11th IAPR-TC-15 internationalworkshop on graph-based Representation in patternrecognition, GbRPR 2017, held in Anacapri, Italy, in May 2017. the 25 full papers and 2 abstracts of invited papers presented in this volume were carefully reviewed and selected from 31 submissions. the papers discuss research results and applications in the intersection of patternrecognition, image analysis, graphtheory, and also the application of graphs to patternrecognition problems in other fields like computational topology, graphic recognition systems and bioinformatics.
In contrast to statistical representations, graphs offer some inherent advantages when it comes to handwriting representation. that is, graphs are able to adapt their size and structure to the individual handwriting a...
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ISBN:
(数字)9783030200817
ISBN:
(纸本)9783030200817;9783030200800
In contrast to statistical representations, graphs offer some inherent advantages when it comes to handwriting representation. that is, graphs are able to adapt their size and structure to the individual handwriting and represent binary relationships that might exist within the handwriting. We observe an increasing number of graph-based keyword spotting frameworks in the last years. In general, keyword spotting allows to retrieve instances of an arbitrary query in documents. It is common practice to optimise keyword spotting frameworks for each document individually, and thus, the overall generalisability remains somehow questionable. In this paper, we focus on this question by conducting a cross-evaluation experiment on four handwritten historical documents. We observe a direct relationship between parameter settings and the actual handwriting. We also propose different ensemble strategies that allow to keep up with individually optimised systems without a priori knowledge of a certain manuscript. Such a system can potentially be applied to new documents without prior optimisation.
this paper describes a procedure for data extraction and interpretation of section representations in vectorized line drawings. Vectorized drawings are considered as a graph representation. the hatch areas are analyse...
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