The size of radial vector for a given pattern increases as the pattern size increases due to increased perimeter of pattern under test. The pattern can be ideally reconstructed using all the radial vectors. However, t...
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ISBN:
(纸本)9781509062188
The size of radial vector for a given pattern increases as the pattern size increases due to increased perimeter of pattern under test. The pattern can be ideally reconstructed using all the radial vectors. However, the vector size may be optimized in order to reconstruct the pattern of the same quality as in an ideal case. In the presented work, the radial vector size is optimized using the statistical analysis of radii profile based on standard deviation, area and perimeter. The reconstructed pattern is approximated to its maximum towards the original pattern by maintaining the standard deviation, area and perimeter. The radii profile in each quadrant is used to get the extremes and figure aspect of the pattern. All the radii are computed about the centre of mass of the pattern under test.
A new deterministic method to determine primality of any given number is presented in this paper. The underlying principle involves the use of a special series that generates lesser prime numbers till the root of the ...
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ISBN:
(纸本)3540287574
A new deterministic method to determine primality of any given number is presented in this paper. The underlying principle involves the use of a special series that generates lesser prime numbers till the root of the number under scrutiny, Subsequently, divisibility is performed to check whether the number is prime or not. Such a series characteristically produces all the successive prime numbers along with a few composite numbers as well, the proportion of latter increasing as one moves to higher numbers, This technique is provably more efficient than other deterministic methods that employ division by primes till the root of the number, either by generating those smaller primes or storing them or by simply taking all odd numbers till the square root.
Bayesian Gaussian processes are known as 'smoothing devices' and in the case of n data points they require O(n(2))... O(n(3)) number of multiplications in order to perform a regression analysis. In this work w...
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ISBN:
(纸本)3540287574
Bayesian Gaussian processes are known as 'smoothing devices' and in the case of n data points they require O(n(2))... O(n(3)) number of multiplications in order to perform a regression analysis. In this work we consider one-dimensional regression with Wiener-Levy (Brownian motion) covariance functions. We indicate that they require only O(n) number of multiplications and show how one can utilize input deformations in order to define a much broader class of efficient covariance functions suitable for discontinuity-preserving filtering. An example of the selective smoothing is presented which shows that regression with Brownian motion filters outperforms or improves nonlinear diffusion filtering especially when observations are contaminated with noise of larger variance.
In this paper an intrusion detection algorithm based on GP ensembles is proposed. The algorithm runs on a distributed hybrid multi-island model-based environment to monitor security-related activity within a network. ...
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ISBN:
(纸本)3540287574
In this paper an intrusion detection algorithm based on GP ensembles is proposed. The algorithm runs on a distributed hybrid multi-island model-based environment to monitor security-related activity within a network. Each island contains a cellular genetic program whose aim is to generate a decision-tree predictor, trained on the local data stored in the node. Every genetic program operates cooperatively, yet independently by the others, by taking advantage of the cellular model to exchange the outmost individuals of the population. After the classifiers are computed, they are collected to form the GP ensemble. Experiments on the KDD Cup 1999 Data show the validity of the approach.
This article delves into an innovative radar working patternrecognition algorithm based on multi-layer perceptron (MLP). Through carefully designed optimization algorithms, we systematically searched and determined t...
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ISBN:
(纸本)9798400716959
This article delves into an innovative radar working patternrecognition algorithm based on multi-layer perceptron (MLP). Through carefully designed optimization algorithms, we systematically searched and determined the optimal MLP network structure to solve the radar operating patternrecognition problem. In a detailed simulation experiment, we carefully analyzed the effects of various network parameters, including the number of network layers, number of neurons, learning rate, and batch rate. The experimental results show that the MLP network can exhibit optimal performance when the number of layers is 5, the number of neurons is 512, the learning rate is 0.006, and the batch rate is 10. This discovery provides us with a highly promising solution to the problem of radar working patternrecognition.
This paper discusses how to develop automatic recognition and count system for urine-sediment visual components. With the help of image processing technology, image segmentation, representation and description, geomet...
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ISBN:
(纸本)9781424464968
This paper discusses how to develop automatic recognition and count system for urine-sediment visual components. With the help of image processing technology, image segmentation, representation and description, geometric features and texture features have been extracted. The urine-sediment visual components are categorized and counted through micro-image automatic recognition and count system with neural network classifier based on genetic algorithm.
In this paper, the optimal projection recognition (OPR) developed in our lab has been used to find the regularities of forming dendritic Co3O4 superstructures. The criteria for predicting dendritic Co3O4 superstructur...
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ISBN:
(纸本)9783037856208
In this paper, the optimal projection recognition (OPR) developed in our lab has been used to find the regularities of forming dendritic Co3O4 superstructures. The criteria for predicting dendritic Co3O4 superstructures can be obtained by using OPR method among different kinds of patternrecognition diagrams. The new samples predicted to be dendritic Co3O4 superstructures were designed by using the inverse projection based on the OPR method. The predicted results agreed well with our experiments. Therefore, the work presented is very useful not only inthe shape-controlled synthesis of dendritic Co3O4 superstructures but also in materials design of other nanomaterials.
This paper proposes a Thai vehicle license plate recognition system, called the hierarchical cross-correlation ARTMAP. An ability to separately train each segment of the network gives the hierarchical cross-correlatio...
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ISBN:
(纸本)9781424401956
This paper proposes a Thai vehicle license plate recognition system, called the hierarchical cross-correlation ARTMAP. An ability to separately train each segment of the network gives the hierarchical cross-correlation ARTMAP an advantage over the other approaches. The experimental results show that the hierarchical cross-correlation ARTMAP outperforms the other approaches by a wide margin.
A robust, efficient segmentation algorithm for automatic segmentation of MR images of the metacarpophalangeal joint is presented. A preliminary segmentation detects bones in MR scans and uses histogram analysis, morph...
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ISBN:
(纸本)3540288333
A robust, efficient segmentation algorithm for automatic segmentation of MR images of the metacarpophalangeal joint is presented. A preliminary segmentation detects bones in MR scans and uses histogram analysis, morphological operations and knowledge based rules to classify various tissues in the joint. The second part of the algorithm improves the segmentation mask and refines boundaries of bones using minimization of a sum of square deviations, automatic signal segmentation into an optimum number of segments, graph theory, and statistical analysis. The algorithm has been tested on 9 MR patient studies and detects 97% of all existing bones correctly with an average exceeding 80% mutual overlap between ground truth and detected regions.
In this article we propose simple descriptor for the purposes of 3D objects recognition and classification. Princeton Shape Benchmark 2004 is used for testing the proposed descriptor. Small size (512b) of the proposed...
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ISBN:
(纸本)3540288333
In this article we propose simple descriptor for the purposes of 3D objects recognition and classification. Princeton Shape Benchmark 2004 is used for testing the proposed descriptor. Small size (512b) of the proposed descriptor and short generation and comparison times combine with relatively high recognition abilities. Surprisingly, we found that despite its simplicity and the small size the proposed descriptor took the first place in "coarser" classification test, where all 3D models were divided into 6 large classes: buildings, household, plants, animals, furniture, vehicles and a miscellaneous class not included in averaged retrieval results.
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