The paper presents the results of the investigation of the I. Boaventura und A. Gonzaga integrated performance evaluation method of edge detection [1-2], obtained using the bundled software of stochastic simulation &q...
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ISBN:
(纸本)9781467374880
The paper presents the results of the investigation of the I. Boaventura und A. Gonzaga integrated performance evaluation method of edge detection [1-2], obtained using the bundled software of stochastic simulation "CS sF" [3]. The methods and approaches of stochastic simulation were used in the experiments and the reference images were approximated with the two-dimensional renewal stream [4-7]. The performance of the outline drawing detection was evaluated by Boaventura und Gonzaga method for three algorithms of the edge detection ("Canny", "Marr-Hildreth" and "ISEF") under different levels of peak signal-to-noise ratio. The results of the investigation are presented as dependences of the estimate probability of the correct edge detection, the type 1 and 2 errors, on S/N ratio. The performance analysis of the above three algorithms for the images, produced on the basis of morphology type "A" and "F", is done based on the performed evaluation.
In this paper we discuss the shortest augmenting path method for solving assignment problems in the following respect:we introduce this basic concept using matching theory we present several efficient labeling techniq...
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The paper presents the results of a quantitative estimation of the edge detection quality using modified Pratt-Yaskorskiy criterion, as well as generalization and adaptation of both approaches based on the generalized...
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ISBN:
(纸本)9783319452425;9783319452432
The paper presents the results of a quantitative estimation of the edge detection quality using modified Pratt-Yaskorskiy criterion, as well as generalization and adaptation of both approaches based on the generalized quality criterion as part of "CS sF" stochastic simulation software package. The reference images are approximated by the two-dimensional high rise renewal stream offering the stationarity properties with no aftereffects and ordinariness. The efficiency of the proposed metrics is considered for three edging algorithms (Marr-Hildreth, ISEF and Canny) at different levels of the additive normal noise. The estimated errors of the first and second kind are given, which allow referring to the efficiency of the proposed generalized quality criterion.
The essay outlines one particular possibility of efficient evaluating the Performance of edge detector algorithms. Three generally known and published algorithms (Canny, Marr, Shen) were analysed by way of example. Th...
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ISBN:
(纸本)9781479945306
The essay outlines one particular possibility of efficient evaluating the Performance of edge detector algorithms. Three generally known and published algorithms (Canny, Marr, Shen) were analysed by way of example. The analysis is based on two-dimensional signals created by means of two-dimensional Semi-Markov Model and subsequently provided with an additive Gaussian noise component. Five quality metrics allow an objective comparison of the algorithms.
When facing a typical pattern recognition task, one usually comes up with a number of so-called features: properties that describe the objects to be recognised. Based on these features, the task of the classifier buil...
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When facing a typical pattern recognition task, one usually comes up with a number of so-called features: properties that describe the objects to be recognised. Based on these features, the task of the classifier building algorithm is to find useful rules that are suitable for the recognition of new objects.
Feature selection is a process where one tries to identify the useful features from among a potentially large set of candidates. The task is notoriously hard, and researchers have been tackling it already for decades. Solving the problem properly might today be more important than ever before, because in many applications, dataset sizes seem to grow faster than does the processing power of computers. For example, in the domain of genetic microarray data, there can easily be thousands of features.
Several research groups have published comparisons aiming to identify the feature selection method that is universally the best. Unfortunately, too often the way that such comparisons are done is just plain wrong. Based on the results of such studies, the computationally intensive search algorithms seem to perform much better than the simple approaches. However, it is shown in this thesis that when the comparison is done properly, it very often turns out that the simple and fast algorithms give results that are just as good, if not even better.
In addition, many studies suggest that excluding some of the features is much more useful than it actually is. This observation is relevant in practice, because the selection process typically takes a lot of time and computing resources - therefore, it would be very convenient not to have to carry it out at all. This thesis shows that the benefits obtained may be negligible compared to what has been presented previously, provided that they are measured correctly.
Moreover, the thesis presents a better-performing approach for accuracy estimation in case the amount of data is small. Further, extensions are discussed from feature se
A system for the compression of data files, viewed as strings of characters, is presented. The method is general, and applies equally well to English, to PL/I, or to digital data. The system consists of an encoder, an...
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A system for the compression of data files, viewed as strings of characters, is presented. The method is general, and applies equally well to English, to PL/I, or to digital data. The system consists of an encoder, an analysis program, and a decoder. Two algorithms for encoding a string differ slightly from earlier proposals. The analysis program attempts to find an optimal set of codes for representing substrings of the file. Four new algorithms for this operation are described and compared. Various parameters in the algorithms are optimized to obtain a high degree of compression for sample texts. [ABSTRACT FROM AUTHOR]
A new text classification algorithm has been put forward based on basic support vector machine *** SVM-KNN algorithm for text classification has been proposed which combined SVM algorithm and KNN *** SVMKNN algorithm ...
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A new text classification algorithm has been put forward based on basic support vector machine *** SVM-KNN algorithm for text classification has been proposed which combined SVM algorithm and KNN *** SVMKNN algorithm can improve the performance of classifier by the feedback and improvement of classifying prediction *** actual effect of SVM-KNN algorithm is tested and the performance is proved in related Chinese web page classification test system.
Predictive accuracy claims should give explicit descriptions of the steps followed, with access to the code used. This allows referees and readers to check for common traps, and to repeat the same steps on other data....
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ISBN:
(纸本)9781920682415
Predictive accuracy claims should give explicit descriptions of the steps followed, with access to the code used. This allows referees and readers to check for common traps, and to repeat the same steps on other data. Feature selection and/or model selection and/or tuning must be independent of the test data. For use of cross-validation, such steps must be repeated at each fold. Even then, such accuracy assessments have the limitation that the target population, to which results will be applied, is commonly different from the source population. Commonly, it is shifted forward in time, and it may differ in other respects also.A consequence of source/target differences is that highly sophisticated modeling may be pointless or even counter-productive. At best, model effects in the target population may be broadly similar. Investigation of the pattern of changes over time is required. Such studies are unusual in the data mining literature, in part because relevant data have not been *** recent investigations are noted that shed interesting light on the comparison between observational and experimental studies, with particular relevance when there is an interest in giving parameter estimates a causal *** mining activity would benefit from wider co-operation in the development and deployment of computing tools, and from better integration of those tools into the publication process.
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