patterns in normal abdominal movement captured with medical imaging can be recognised by a trained radiologist but the process is time consuming. Abdominal adhesions present a diagnostic problem in which the radiologi...
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ISBN:
(纸本)9783642040306
patterns in normal abdominal movement captured with medical imaging can be recognised by a trained radiologist but the process is time consuming. Abdominal adhesions present a diagnostic problem in which the radiologist is asked to detect abnormal movement that may be indicative of pathology. this paper postulates that the use of image analysis call augment the diagnostic abilities of the radiologist in respect of adhesions. Proof of concept experiments were conducted in-silico to explore the effectiveness of the technique. the results indicate that trained participants are accurate in their assessment of abnormalities when supplied with additional information from image analysis techniques. However without the additional information, participants made incorrect diagnoses on many occasions. ROC methods were used to quantify the outcomes of the in-silico experiment.
Binary fingerprints encoding the presence of 2D fragment substructures in molecules are extensively used for similarity-based virtual screening in the agrochemical and pharmaceutical industries. this paper describes t...
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ISBN:
(纸本)9783642040306
Binary fingerprints encoding the presence of 2D fragment substructures in molecules are extensively used for similarity-based virtual screening in the agrochemical and pharmaceutical industries. this paper describes two techniques for enhancing the effectiveness of screening: the use of a second-level search based on the nearest neighbours of the initial reference structure;and the use of weighted fingerprints encoding the frequency of occurrence, rather than just the mere presence, of substructures. Experiments using several databases for which both structural and bioactivity data are available demonstrate the effectiveness of these two approaches.
this paper investigates the effect of various feature extraction methods on the recognition ability of a self-organising neural network called Paradise when applied to the problems of the classification of face images...
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this paper investigates the effect of various feature extraction methods on the recognition ability of a self-organising neural network called Paradise when applied to the problems of the classification of face images and hand written character recognition. the feature extraction methods investigated are, oriented Gaussian filters, Gabor filters and oriented Laplacian of Gaussian (LoG) filters. the recognition results for the two applications are Shown to compare favourably with other techniques designed specifically for the two tasks. (C) 2000 Civil-Comp Ltd. and Elsevier Science Ltd. All rights reserved.
recognition of specific functionally-important DNA sequence fragments is considered one of the most important problems in bioinformatics. One type of such fragments are promoters, Le., short regulatory DNA sequences l...
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ISBN:
(纸本)9781424417391
recognition of specific functionally-important DNA sequence fragments is considered one of the most important problems in bioinformatics. One type of such fragments are promoters, Le., short regulatory DNA sequences located upstream of a gene. Detection of promoters in DNA sequences is important for successful gene prediction. In this paper, a machine learning method, called Support Vector Machine (SVM), is used for classification of DNA sequences and promoter recognition. For optimal classification, 11 rules for mapping of DNA sequences into binary SVM feature space are analyzed. Classification is performed using a power series kernel function. Kernel parameters are optimized using a modification of the Nelder-Mead (downhill simplex) optimization method. the results of classification for drosophila and human sequence datasets are presented.
In this paper, we address the problem of defining and modeling the handwriting signal using its geometrical and spatio-temporal features, in order to improve the recognition task. We use the frequent pattern methods t...
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ISBN:
(纸本)9781538652398
In this paper, we address the problem of defining and modeling the handwriting signal using its geometrical and spatio-temporal features, in order to improve the recognition task. We use the frequent pattern methods to enhance the quality of the signature vector extracted from the handwritten character. Two types of frequent patterns are employed to represent the handwritten characters pertinently: the maximal and closed frequent patterns. We created a new database that contains words of two different letters. the generated results are very promising, through which we have demonstrated that the "minimum threshold", which is an essential parameter in the frequent patterns mining algorithms, represent a key feature in the characters description.
One-class classification, which was tested successfully in unbalanced sample classification problems, is one of the hotspots in patternrecognition research. this paper first analysis the commonly used one-class class...
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ISBN:
(纸本)9781728136608
One-class classification, which was tested successfully in unbalanced sample classification problems, is one of the hotspots in patternrecognition research. this paper first analysis the commonly used one-class classification methods, then classifies these methods into three categories: boundary based method, re-construction based method and border based method. Finally, a series of testing experiments based on artificial database are designed to test the advantages and disadvantages of these methods from the aspect of learning ability, classification decision and algorithm complexity.
Following the fourth edition of the workshop on Reproducible Research in patternrecognition (RRPR) at the internationalconference on patternrecognition (ICPR), this paper reports the main discussions that were held...
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Summary form only given. My presentation contains a review of recent results of development of analog optical patternrecognition methods which are based on examples of transparent (all-optical or hybrid) setup of opt...
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In this article we shortly present new string pattern matching algorithm. the algorithm uses novel technique for skipping unnecessary comparisons in pattern searching phase. the pattern searching is applied in almost ...
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ISBN:
(纸本)9789532900910
In this article we shortly present new string pattern matching algorithm. the algorithm uses novel technique for skipping unnecessary comparisons in pattern searching phase. the pattern searching is applied in almost all branches of science such as bioinformatics, information security, text mining, etc. In the context of continuous increase of data, efficient algorithms are necessary to ensure that one can find a pattern in a sequence in a fast and accurate manner. pattern searching solves the problem of finding a pattern exhibiting certain properties within a given sequence of symbols. Concept of the new algorithm presented in this article is based on a character index in a pattern, aiming at, but not limited to patterns in DNA sequences.
A microbial bioflim is structured mainly by a protective sticky matrix of extracellular polymeric substances. the appreciation of such structures is useful for the microbiologist and can be subjective to the observer....
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ISBN:
(纸本)9783642040306
A microbial bioflim is structured mainly by a protective sticky matrix of extracellular polymeric substances. the appreciation of such structures is useful for the microbiologist and can be subjective to the observer. thus, quantifying the underlying images in useful parameters by means of an objective image segmentation process helps substantially to reduce errors in quantification. this paper proposes an approach to segmentation of biofilm images rising optimal multilevel thresholding and indices of clustering validity. A comparison of automatically segmented images with manual segmentation is done through different thresholding criteria, and clustering validity indices are used to find the correct number of thresholds, obtaining results similar to the segmentation done by an expert.
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