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73 results for “Pattern Classification”
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Research ArticleOpen accessPhrase in the titleNew Constructive Neural Network Architecture for Pattern ClassificationS. S. Sridhar, M. PonnavaikkoProblem statement: Constructive neural network learning algorithms provide optimal ways to determine the architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classification problems. These algorithms initially start with small network and dynamically allow the network to grow by adding and training neurons as needed until a satisfactory solution is found. The … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,565 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePattern Classification: An Improvement Using Combination of VQ and PCA Based TechniquesAlok Sharma, Kuldip K. Paliwal, Godfrey C. OnwuboluThis study firstly presents a survey on basic classifiers namely Minimum Distance Classifier (MDC), Vector Quantization (VQ), Principal Component Analysis (PCA), Nearest Neighbor (NN) and K-Nearest Neighbor (KNN). Then Vector Quantized Principal Component Analysis (VQPCA) which is generally used for representation purposes is considered for performing classification tasks. Some classifiers achieve high classification accuracy but their data storage requirement and … …American Journal of Applied Sciences, Vol. 2, Issue 10 · 31 Oct 2005 · 6,498 accessesView PDFCite
Research ArticleOpen accessIn the keywordsConvolution Neural Networks of Dynamically Sized Filters with Modified Stochastic Gradient Descent Optimizer for Sound ClassificationManu Pratap Singh, Pratibha RashmiDeep Neural Networks (DNNs), specifically Convolution Neural Networks (CNNs) are found well suited to address the problem of sound classification due to their ability to capture the pattern of time and frequency domain. Mostly the convolutional neural networks are trained and tested with time-frequency patches of sound samples in the form of 2D pattern vectors. Generally, existing pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 1 · 13 Dec 2023 · 5,781 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Hidden Genetic Layer Based Neural Network for Mobility PredictionL. Velmurugan, P. ThangarajProblem statement: With numerous wireless devices increasingly connecting to the internet, WLAN infrastructure planning becomes very important to maintain desired quality of services. For maintaining desired quality of service it is desirable to know the movement pattern of users. Mobility prediction involves finding the mobile device's next access point as it moves through the wireless network. Hidden Markov models and … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 11 Feb 2012 · 7,224 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEffect of Hidden Layer Neurons on the Classification of Optical Character Recognition Typed Arabic NumeralsNidal F. Shilbayeh, Mahmoud Z. IskandaraniProblem statement: The effect of varying the number of nodes in the hidden layer and number of iterations are important factors in the recognition rate. In this paper, a novel and effective criterion based on Cross Pruning (CP) algorithm is proposed to optimize number of hidden neurons and number of iterations in Multi Layer Perceptron (MLP) neural based recognition system. … …Journal of Computer Science, Vol. 4, Issue 7 · 31 Jul 2008 · 7,556 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRule Extraction from Radial Basis Functional Neural Networks by Using Particle Swarm OptimizationM. R. Senapati, I. Vijaya, P. K. DashRadial basis functional neural networks (RBFNN) provide an outstanding possibility for generating rules for solving pattern classification problems. One of the most important factors in RBFNN is finding out the center and spread. This paper examines rules extracted from RBF networks trained by Particle swarm Optimization (PSO). The selection of the RBFNN centers, spreads and the network weights can be … …Journal of Computer Science, Vol. 3, Issue 8 · 31 Aug 2007 · 6,784 accessesView PDFCite
Research ArticleOpen accessIn the keywordsClassification of Finger Vein Image Using Convolutional Neural NetworkAhmed S. Hameed, Shawkat K. Guirguis, Hend A. ElsayedCurrently available technologies can perform rather well, but their effectiveness is mostly contingent on how well the venous images being analyzed are quality images. Finger vein features have garnered significant attention in the past few years as a potential means of automatic user identification. A significant amount of daily usage goes into the very vital personal identification procedure. The identification … …Journal of Computer Science, Vol. 21, Issue 2 · 6 Jan 2025 · 4,712 accessesView PDFCite
Research ArticleOpen accessIn the keywordsClassification of Normal and Abnormal Lung CT-scan Images Using Cellular Learning AutomataNooshin Hadavi, Md Jan Nordin, Ali Shojaeipour, Mohammad Faidzul NasrudinThis paper proposes a medical pattern recognition system based on the Cellular automata (CA). CA or cellular machine is a dynamic mathematical model that consists of several similar and simple units organized by considerably simple local rules. Each cell acts as a simple computer automaton. This can lead to the implementation of the complex computations through uncomplicated methods. However, the … …Journal of Computer Science, Vol. 16, Issue 1 · 15 Jan 2020 · 7,834 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Deep Convolutional Neural Wavelet Network for Classification of Medical ImagesRamzi Ben Ali, Ridha Ejbali, Mourad ZaiedThis work present a new solution for medical image classification using the Neural Network (NN) and Wavelet Network (WN) based on the Fast Wavelet Transform (FWT) and the Adaboost algorithm. This method is divided in two stages: The learning stage and the classification stage. The first consists to extract the features using the FWT based on the MultiResolution Analysis (MRA). … …Journal of Computer Science, Vol. 14, Issue 11 · 11 Nov 2018 · 7,620 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe Classification Model of Sandals Dhiif’s Product with Back Propagation and Fourier Descriptors MethodWikaria Gazali, Haryono Soeparno, Ngarap Im ManikClassification is a vital process in every industry. While manual classification is inefficient in terms of cost and time, the computerized techniques offer better and faster solution on this matter. Fourier Descriptors is the mathematical formulas to save objects in functions of Fourier series. While back propagation is an Artificial Neural Network (ANN) method to recognize patterns and images through … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 6,370 accessesView PDFCite