this book constitutes the refereed proceedings of the 5th INNS IAPR TC3 GIRPR internationalworkshop on Artificial Neural Networks in patternrecognition, ANNPR 2012, held in Trento, Italy, in September 2012. the 21 r...
ISBN:
(数字)9783642332128
ISBN:
(纸本)9783642332111
this book constitutes the refereed proceedings of the 5th INNS IAPR TC3 GIRPR internationalworkshop on Artificial Neural Networks in patternrecognition, ANNPR 2012, held in Trento, Italy, in September 2012. the 21 revised full papers presented were carefully reviewed and selected for inclusion in this volume. they cover a large range of topics in the field of neural network- and machine learning-basedpatternrecognition presenting and discussing the latest research, results, and ideas in these areas.
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.
Accurate detection of lip contour is important in many application areas, including biometric authentication, human computer interaction, and facial expression recognition. In this paper, we propose a new lip boundary...
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We propose a meta-algorithm for registration improvement by combining deformable image registrations (MetaReg). It is inspired by a well-established method from machine learning, the combination of classifiers. MetaRe...
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In the field of structural patternrecognitiongraphs constitute a very common and powerful way of representing objects. the main drawback of graphrepresentations is that the computation of various graph similarity m...
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ISBN:
(纸本)9783642208447
In the field of structural patternrecognitiongraphs constitute a very common and powerful way of representing objects. the main drawback of graphrepresentations is that the computation of various graph similarity measures is exponential in the number of involved nodes. Hence, such computations are feasible for rather small graphs only. One of the most flexible graph similarity measures is graph edit distance. In this paper we propose a novel approach for the efficient computation of graph edit distance based on bipartite graph matching by means of the Volgenant-Jonker assignment algorithm. Our proposed algorithm provides only suboptimal edit distances, but runs in polynomial time. the reason for its sub-optimality is that edge information is taken into account only in a limited fashion during the process of finding the optimal node assignment between two graphs. In experiments on diverse graphrepresentations we demonstrate a high speed up of our proposed method over a traditional algorithm for graph edit distance computation and over two other sub-optimal approaches that use the Hungarian and Munkres algorithm. Also, we show that classification accuracy remains nearly unaffected by the suboptimal nature of the algorithm.
In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from diff...
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ISBN:
(纸本)9783642208447
In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from different (granularity) levels are combined to a final (better) segmentation with user-specified operations guiding the segmentation process. based on these operations the users can produce a final image segmentation that best suits their applications. this work can be used for applications where we need accuracy in image segmentation, in annotating images or creating ground truth among others.
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.
In this study we propose a strategy for the follow-up of the process behavior and detection of failures. An approach of industrial diagnosis based on the statistical patternrecognition Neuro-Fuzzy being based on a di...
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ISBN:
(纸本)9788890372476
In this study we propose a strategy for the follow-up of the process behavior and detection of failures. An approach of industrial diagnosis based on the statistical patternrecognition Neuro-Fuzzy being based on a digital representation and symbolic system of the forms is implemented. Within this framework, data-processing interactive software of simulation baptized NEFDIAG (NEuro Fuzzy DIAGnosis) version 1.0 is developed. this software devoted primarily to creation, training and test of a classification Neuro-Fuzzy system of industrial process failures. NEFDIAG can be represented like a special type of fuzzy perceptron, withthree layers used to classify patterns and failures. the system selected is the workshop of SCIMAT clinker, cement factory in Algeria.
the proceedings contain 7 papers. the topics discussed include: better drilling through sensor analytics: a case study in live operational intelligence;gas sensor drift mitigation using classifier ensembles;design con...
ISBN:
(纸本)9781450308328
the proceedings contain 7 papers. the topics discussed include: better drilling through sensor analytics: a case study in live operational intelligence;gas sensor drift mitigation using classifier ensembles;design considerations for the WISDM smart phone-based sensor mining architecture;supervised and semi-supervised online boosting tree for industrial machine vision application;precise anytime clustering of noisy sensor data with logarithmic complexity;patternrecognition and classification for multivariate time series;and identifying user traits by mining smart phone accelerometer data.
the proceedings contain 37 papers. the topics discussed include: enhancing cooperation in distributed information systems using conviviality and multi-context systems;a rule based approach to group recommender systems...
ISBN:
(纸本)9783642257247
the proceedings contain 37 papers. the topics discussed include: enhancing cooperation in distributed information systems using conviviality and multi-context systems;a rule based approach to group recommender systems;combining collaborative filtering and sentiment classification for improved movie recommendations;automatic composition and mediation on multiple-language semantic web services;fuzzy-based trusted ant routing (FTAR) protocol in mobile ad hoc networks;pattern synthesis using fuzzy partitions of the feature set for nearest neighbor classifier design;crisp and soft clustering of mobile calls;handwritten Kannada vowel character recognition using crack codes and Fourier descriptors;PCA plus LDA on wavelet co-occurrence histogram features: application to CBIR;printed text characterization for identifying print technology using expectation maximization algorithm;and forecasting using rules extracted from privacy preservation neural network.
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