In this paper a vertical repositioning method based on the center of gravity is investigated for handwriting recognition systems and evaluated on databases containing Arabic and French handwriting. Experiments show th...
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ISBN:
(纸本)9780769547749;9781467322621
In this paper a vertical repositioning method based on the center of gravity is investigated for handwriting recognition systems and evaluated on databases containing Arabic and French handwriting. Experiments show that vertical distortion in images has a large impact on the performance of HMM based handwriting recognition systems. Recently good results were obtained with Bernoulli HMMs (BHMMs) using a preprocessing with vertical repositioning of binarized images. In order to isolate the effect of the preprocessing from the BHMM model, experiments were conducted with Gaussian HMMs and the LSTM-RNN tandem HMM approach with relative improvements of 33% WER on the Arabic and up to 62% on the French database.
this paper investigates the use of static and dynamic neural networks in phoneme recognition. Besides this, the paper also proposes a cooperative static and dynamic neural networks model. the cooperative model integra...
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ISBN:
(纸本)9781467316583
this paper investigates the use of static and dynamic neural networks in phoneme recognition. Besides this, the paper also proposes a cooperative static and dynamic neural networks model. the cooperative model integrates a decision system for phoneme recognition. Mel cepstrum coding has been applied to represent speech signal in frames. Features from the selected frames are used to train neural networks based models. the comparative study show that the proposed cooperative model provides more accurate recognition rates both in auto-coherence test and generalization test.
the proceedings contain 34 papers. the topics discussed include: human sign recognition for robot manipulation;fuzzy sets for human fall patternrecognition;vision system for 3D reconstruction with telecentric lens;a ...
ISBN:
(纸本)9783642311482
the proceedings contain 34 papers. the topics discussed include: human sign recognition for robot manipulation;fuzzy sets for human fall patternrecognition;vision system for 3D reconstruction with telecentric lens;a tool for hand-sign recognition;improving the multiple alignments strategy for fingerprint verification;breaking reCAPTCHAs with unpredictable collapse: heuristic character segmentation and recognition;using short-range interactions and simulated genetic strategy to improve the protein contact map prediction;associative model for solving the wall-following problem;the list of clusters revisited;a heuristically perturbation of dataset to achieve a diverse ensemble of classifiers;compact and efficient permutations for proximity searching;and NURBS parameterization: a new method of parameterization using the correlation relationship between nodes.
Vision-based fall detection is a challenging problem in patternrecognition. this paper introduces an approach to detect a fall as well as its type in infrared video sequences. the regions of interest of the segmented...
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We introduce a new, powerful query formulation formalism for complex, multivariate sequence data. the new query language, termed pattern graphs, is capable of reflecting more aspects of temporal patterns than earlier ...
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the paper presents two applications of a neurofuzzy system for solving complex problems in power engineering, the recognition of power quality disturbances and the stability of power generation. the neuro-fuzzy system...
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ISBN:
(纸本)0889863237
the paper presents two applications of a neurofuzzy system for solving complex problems in power engineering, the recognition of power quality disturbances and the stability of power generation. the neuro-fuzzy system combines the powerful capability of Learning Vector Quantization networks in patternrecognition withthe flexibility of the Fuzzy Associative Memory rulematrix in dealing with uncertainties. the paper also describes results of the system evaluation, which demonstrate the high performance of the system.
In this paper we study the robustness of our CAD system, since this is one of the main factors that determine its quality. A CAD system must guarantee consistent performance over time and in various clinical situation...
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DNA microarrays have contributed to the exponential growth of genetic data from years. One of the possible applications of this large amount of gene expression data diagnosis of diseases like cancer using classificati...
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ISBN:
(纸本)9783642288388
DNA microarrays have contributed to the exponential growth of genetic data from years. One of the possible applications of this large amount of gene expression data diagnosis of diseases like cancer using classification methods. In turn, explicit biological knowledge about gene functions has also grown tremendously over the last decade. this work integrates explicit biological knowledge in classification process using Rough Set theory, making it more effective. In addition, the proposed model is able to indicate which part of biological knowledge has been used building the model and classifing new samples.
the present work presents a novel solution to provide descriptors of a texture image with application in the classification of such images. the proposed method is based on the lacunarity measure of an image. We apply ...
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this study is aiming to develop a novel patternrecognition approach for identifying the cold and hot properties of Chinese medicinal herbs. All associated target proteins in the herbs with different properties were o...
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