Face recognition is a system that identifies human faces from an image database or from a video frame . The paper presents a literature review on face recognition approaches. It then explains two different algorithms for feature extraction which are Principal Component Analysis and Fisher Faces algorithm. It also explains how images can be recognized using a Backpropagation algorithm on a Feedf...

objective(s): this study aims to evaluate and predict the thermal conductivity of iron oxide nanofluid at different temperatures and volume fractions by artificial neural network (ann) and correlation using experimental data. methods: two-layer perceptron feedforward artificial neural network and backpropagation levenberg-marquardt (bp-lm) training algorithm are used to predict the thermal cond...

Historical manuscripts are one of documents that important to be preserved because they contain a lot information, example them is script as the historical . document mostly still use handwriting in so many reserch. Currently, there research regarding preservation characters. One way can used digitization process. Digitizing’s process tanable by recognizing existing information using technology...

Neural networks are a popular tool in the area of pattern recognition. However, since a very large number of neural network architectures exist, it has not been established which one is the most efficient. In this paper we compare the performance of three neural network architectures: Kohonen’s self-organizing network, probabilistic neural network, and a modified backpropagation applied to a si...

The artificial neural networks, the learning algorithms and mathematical models mimicking the information processing ability of human brain can be used non-linear and complex data. The aim of this study was to predict the breeding values for milk production trait in Iranian Holstein cows applying artificial neural networks. Data on 35167 Iranian Holstein cows recorded between 1998 to 2009 were ...

In this paper the Sigma-if artificial neural network model is considered, which is a generalization of an MLP network with sigmoidal neurons. It was found to be a potentially universal tool for automatic creation of distributed classification and selective attention systems. To overcome the high nonlinearity of the aggregation function of Sigma-if neurons, the training process of the Sigma-if n...

The neural network is popular and used in many areas within the financial field, such as credit authorization screenings, regularities in security price movements, simulations of market behaviour, and so forth. In this research, the authors use a neural network technique for stock price forecasting of Great West Life, an insurance company based in Winnipeg, Canada. The Backpropagation algorithm...