This paper addresses an important and vital problem within the general area of character recognition, namely recognizing Marathi handwritten numerals. Artificial neural network approaches have been recognized as a powerful tool for handwritten numeral recognition. This paper demonstrates the use of single hidden layer MLP NN as a classifier for handwritten Marathi Numerals of Devnagari script. ...

For managing data in a smart card’s limited memory, containing medical and biometric images, images compression is resorted to. For image retrieval, it is necessary that the classification algorithm be efficient to search and locate the image in a compressed domain. This study proposes a novel training algorithm for Multi-Layer Perceptron Neural Network (MLP-NN) to classify compressed images. M...

Boaz Lerner*, Hugo Guterman#, Mayer Aladjem#, and Its’hak Dinstein# *University of Cambridge Computer Laboratory, New Museums Site, Cambridge CB2 3QG, UK #Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel Published in Pattern Recognition Letters, vol. 20(1), pp. 7-14, 1999. Abstract The projection maps and derived classification accu...

In this paper, we proposed an efficient method to address the problem of scene understanding that is based on neural network (NN) and image segmentation. We utilized a multilayer perceptron (MLP) to train the network and features are extracted using pixels in the RGB color space. In this work, object samples in images with varying lighting conditions are used to obtain a wide object color distr...

model is proposed to discriminate alcoholics using single trial gamma band Visual Evoked Potential (VEP) signals using 3 different classifiers: Simplified Fuzzy ARTMAP (SFA) neural network (NN), Multilayer-perceptron-backpropagation (MLP-BP) NN and Linear Discriminant (LD). Electroencephalogram (EEG) signals were recorded from alcoholic and control subjects during the presentation of visuals fr...

Nowadays, breast cancer is one of the leading causes death women in worldwide. If detected at beginning stage, it can ensure long-term survival. Numerous methods have been proposed for early prediction this cancer, however, efforts are still ongoing given importance problem. Artificial Neural Networks (ANN) established as some most dominant machine learning algorithms, where they very popular a...

Ensemble of classifiers is one of the most researched methods in pattern classification in recency. It’s a well-known fact that multiple phases for evaluation provides more accuracy. In this paper we proposed a multistage classifier approach where we are applying three supervised classifiers for the classification in pattern recognition. Three Classifiers are Multilayer Perceptron (MLP), K-Near...

A fault diagnosis system in a multilevel-inverter using a compact neural network is proposed in this paper. It is difficult to diagnose a multilevel-inverter drive (MLID) system using a mathematical model because MLID systems consist of many switching devices and their system complexity has a nonlinear factor. Therefore, a neural network classification is applied to the fault diagnosis of a MLI...

A self-organizing neural network model for mechanism of pattern recognition unaected by shift in position. of Japanese Kanji using principal component analysis as a preprocessor to an articial neural etwork. 10 necessary, only one initial guess was used. These results show that for character classication accuracy NN methods and statistical methods have comparable accuracies conrming the COCR re...

The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the ...