This paper presents novel technique for recognizing faces. The proposed method uses hybrid feature extraction techniques such as Chi square and entropy are combined together. Feed forward and self-organizing neural network are used for classification. We evaluate proposed method using FACE94 and ORL database and achieved better performance. Keywords-Biometric; Chi square test; Entropy; FFNN; SOM.

Automatic license plate recognition system is an image processing technology used to identify vehicles by their license plates. Such systems require the recognition of characters from the plate image. Artificial neural networks are commonly used to perform character recognition due to their high noise tolerance. Feed-Forward Neural Network (FFNN) can be used to recognize the characters from ima...

In this paper, we intend to offer a new method based on fuzzy neural networks for finding a real solution of fuzzy equations system. Our proposed fuzzified neural network is a fivelayer feed-back neural network that corresponding connection weights to output layer are fuzzy numbers. The proposed architecture of artificial neural network, can get a real input vector and calculates it’s correspon...

production of highly viscous tar sand bitumen using steam assisted gravity drainage (sagd) with a pair of horizontal wells has advantages over conventional steam flooding. this paper explores the use of artificial neural networks (anns) as an alternative to the traditional sagd simulation approach. feed forward, multi-layered neural network meta-models are trained through the back-error-propaga...

This article presents an approach for data association in single camera, multi-object tracking scenarios using feed-forward neural networks (FFNN). The challenges of data association are object occlusions and changing features which are used to describe objects during the process. The presented algorithm within this article can be applied to any kind of object which has to be tracked, e.g. pers...

The purpose of this paper is to develop an appropriate artificial neural network (ANN) model of induction motor bearing (IMB) failure prediction. Acoustic emission (AE) represented the technique of collecting the data that was collected from the IMB and this data were measured in term of decibel (dB) and Distress level. The data was then used to develop the model using ANN for IMB failure predi...

In the dynamic global economy, the accuracy in forecasting the foreign currency exchange rates is of crucial importance for any future investment. The use of computational intelligence based techniques for forecasting has been proved extremely successful in recent times. The aim of this study is to identify a neural network model which has ability to predict the US Dollar against Sri Lankan Rup...

Agricultural sector area plays major role in Indian economy. This paper shows research comparison in between MLP Feed Forward Neural Network, Generalized Regression Neural Network and Radial-Basis Function Neural Network in the field of Wheat yield prediction using Z-score Normalization method. The outcome represents that GRNN present better prediction results as compared to FFNN and RBNN. Eigh...

Work had always been under process to design efficient algorithms for image compression based on various conventional and soft computing methodologies. This paper aims at exploring the application of multi layered perceptron (MLP) feed forward neural networks (FFNN), wavelet transforms and their combination architectures for image compression. Initially two neural network architectures for imag...