We study the important issue of choosing representationsthat are suitable for recognizing pen based handwriting of characters in Tamil, a language of India. Four different choices, based on the following set of featu...
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the proceedings contain 20 papers. the special focus in this conference is on Biometrics, Document Image Inspection and Applications. the topics include: Voice passphrase variability evaluation for speaker recognition...
ISBN:
(纸本)9783319201245
the proceedings contain 20 papers. the special focus in this conference is on Biometrics, Document Image Inspection and Applications. the topics include: Voice passphrase variability evaluation for speaker recognition;studies in individuality;robust 2d face recognition under different illuminations using binarized partial face features;comparison of multidirectional representations for multispectral palmprint recognition;efficient iris recognition system using relational measures;a study of identification performance of facial regions from CCTV images;inverse of low resolution line halftone images for document inspection;when document security brings new challenges to document analysis;stamp verification for automated document authentication;introducing and analysis of the windows 8 event log for forensic purposes;automatic creation of computer forensic test images;art forgery detection via craquelure pattern matching;forensics acquisition and analysis of instant messaging and VOIP applications and an integrated tool for forensic writer identification.
the proceedings contain 24 papers. the topics discussed include: graph embeddings of dynamic functional connectivity reveal discriminative patterns of task engagement in HCP data;modeling voxel connectivity for brain ...
ISBN:
(纸本)9781467371452
the proceedings contain 24 papers. the topics discussed include: graph embeddings of dynamic functional connectivity reveal discriminative patterns of task engagement in HCP data;modeling voxel connectivity for brain decoding;mind the noise covariance when localizing brain sources with M/EEG;tractography mapping for dissimilarity space across subjects;speeding-up model-selection in graphNet via early-stopping and univariate feature-screening;MEG/EEG source imaging with a non-convex penalty in the time-frequency domain;multivariate effect ranking via adaptive sparse PLS;joint feature extraction from functional connectivity graphs with multi-task feature learning;testing multimodal integration hypotheses with application to schizophrenia data;and automatic brain tumor segmentation from MR images via a multimodal sparse coding based probabilistic model.
the proceedings contain 21 papers. the topics discussed include: how to quantitatively compare data dissimilarities for unsupervised machine learning?;kernel robust soft learning vector quantization;incremental learni...
ISBN:
(纸本)9783642332111
the proceedings contain 21 papers. the topics discussed include: how to quantitatively compare data dissimilarities for unsupervised machine learning?;kernel robust soft learning vector quantization;incremental learning by message passing in hierarchical temporal memory;representative prototype sets for data characterization and classification;feature selection by block addition and block deletion;feature selection by block addition and block deletion;towards a novel probabilistic graphical model of sequential data: fundamental notions and a solution to the problem of parameter learning;towards a novel probabilistic graphical model of sequential data: a solution to the problem of structure learning and an empirical evaluation;statistical recognition of a set of patterns using novel probability neural network;and on graph-associated matrices and their eigenvalues for optical character recognition.
this paper introduces the concept of discrete multidimensional size function, a mathematical tool studying the so-called size graphs. these graphs constitutes an ingredient of Size theory, a geometrical/topological ap...
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ISBN:
(纸本)9783642208447
this paper introduces the concept of discrete multidimensional size function, a mathematical tool studying the so-called size graphs. these graphs constitutes an ingredient of Size theory, a geometrical/topological approach to shape analysis and comparison. A global method for reducing size graphs is presented, together with a theorem stating that size graphs reduced in such a way preserve all the information in terms of multidimensional size functions. this approach can lead to simplify the effective computation of discrete multidimensional size functions, as shown by examples.
this paper presents an approach to derive critical points of a shape, the basis of a Reeb graph, using a combination of a medial axis skeleton and features along this skeleton. A Reeb graph captures the topology of a ...
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the proceedings contain 39 papers. the special focus in this conference is on Grammars, Languages, Morphology and Semantic Nets. the topics include: Efficient recognition of a class of context-sensitive languages desc...
ISBN:
(纸本)3540615776
the proceedings contain 39 papers. the special focus in this conference is on Grammars, Languages, Morphology and Semantic Nets. the topics include: Efficient recognition of a class of context-sensitive languages described by augmented regular expressions;optimal and information theoretic syntactic patternrecognition for traditional errors;the morphic generator grammatical inference methodology and multilayer perceptrons;a hybrid approach to acoustic modeling;two different approaches for cost-efficient viterbi parsing with error correction;bounded parallelism in array grammars used for character recognition;comparison between the inside-outside algorithm and the viterbi algorithm for stochastic context-free grammars;generalized morphological operators applied to map-analysis;extended cascade-correlation for syntactic and structural patternrecognition;including geometry in graphrepresentations;a quadratic-time graph isomorphism algorithm and its applications;an evidential merit function to guide search in a semantic network based image analysis system;inexact graph matching with genetic search;automatic recognition of bidimensional models learned by grammatical inference in outdoors scenes;signal decomposition by multiscale learning algorithms;structural learning of character patterns for on-line recognition of hand-written Japanese characters;recognition of hand-printed characters using induct machine learning;opponent color processing based on neural models;invariants and fixed structures lead the way to change;representing shape by line patterns;surface skeletonization of volume objects;peculiarities of structural analysis of image contours under various orders of scanning and a structural analysis of curve deformation by discontinuous transformations.
In this paper we compare the performance of several popular clustering algorithms, including k-means, fuzzy c-means, hierarchical agglomerative, and graph partitioning. the novelty of this work is that the objects to ...
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ISBN:
(纸本)3540225706
In this paper we compare the performance of several popular clustering algorithms, including k-means, fuzzy c-means, hierarchical agglomerative, and graph partitioning. the novelty of this work is that the objects to be clustered are represented by graphs rather than the usual case of numeric feature vectors. We apply these techniques to web documents, which are represented by graphs instead of vectors, in order to perform web document clustering. Web documents are structured information sources and thus appropriate for modeling by graphs. We will examine the performance of each clustering algorithm when the web documents are represented as bothgraphs and vectors. this will allow us to investigate the applicability of each algorithm to the problem of web document clustering.
作者：
Bloch, ILTCI
Ecole Natl Super Telecommun CNRS UMR 5141Dept TSI F-75013 Paris France
We show in this paper that mathematical morphology provides a unified and consistent framework to express different types of spatial relationships and to answer different questions about them, with good properties. We...
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ISBN:
(纸本)3540310193
We show in this paper that mathematical morphology provides a unified and consistent framework to express different types of spatial relationships and to answer different questions about them, with good properties. We show then how to use these fuzzy relationships in model-basedpatternrecognition and spatial reasoning under imprecision. Two examples are presented, one where recognition of face features is expressed as non bijective correspondence between graphs representing regions and spatial relations, and one where anatomical expert knowledge involving spatial relationships is used to guide the recognition of brain structures.
the problem of text recognition is becoming increasingly important due to the active introduction of digital computing and the widespread use of word processors. patternrecognition is one of the most difficult from a...
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the problem of text recognition is becoming increasingly important due to the active introduction of digital computing and the widespread use of word processors. patternrecognition is one of the most difficult from a mathematical point of view and one of the most popular areas of artificial intelligence programming. In the work is researched approaches and methods of solving text recognition problem, improved the performance of the available algorithms for text recognition and created algorithmic software. According to the analysis, neural networks were selected for handwriting recognition. the main advantage of using neural networks is a good generalization ability, the ability to use context analysis and recognize a symbol based on the surrounding symbols. the software implementation features of Hopfield and convolutional neural network, genetic algorithm, which were chosen as effective methods for recognizing handwritten text, were considered. Algorithmic software and web application that uses these methods for the task of handwritten text recognition is developed.
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