. This paper devoted to an iris recognition system (IRS) designed using 2D-Discrete Cosine Transform (DCT) features and Self Organizing Map (SOM) and Radial Basis Function (RBF) which are an Artificial Neural Network (ANN) used as classifier. DCT is used for feature extraction to capture essential details. SOM and RBF are applied for classification with different functional paradigms. With resp...

Seizure activity takes place due to an irregular excessive electrical action in the human brain. The electrical activity in the form of brain waves (signals) can measured by using the device called Electroencephalogram (EEG). In this paper, we have reviewed our work so far made regarding EEG signals. Comparative between Artificial Neural Network (ANN) and Support Vector Machine (SVM) this revie...

An enhanced medical decision support system for classification of Ultrasound Kidney images is developed for health care and presented in this paper. The image enhancement was done by removing the speckle, salt and pepper noises using fuzzy c means filtering and the Gray Level Coocurrence Matrix was obtained for feature extraction. Gabor wavelets and Histogram equalization were used for the sele...

To extend the functionalities of Advanced Driver Assistance Systems (ADAS) and have a more accurate control on the parameters of sensors mounted on an intelligent vehicle, a tool that can classify the scenarios which the vehicle moves in, is needed. This article presents a comparison of three classification techniques (PCA, ANN and SVM) to obtain a fast and robust scene classifier based only on...

A recent development in the hybrid HMM/ANN speech recognition paradigm is the use of several subword classifiers, each of which provides different information about the speech signal. Although the combining methods have obtained promising results, the strategies so far proposed have been relatively simple. In most cases frame-level subword unit probabilities are combined using an unweighted pro...

Diabetes patients are increasing in number so it is necessary to predict , treat and diagnose the disease. Data Mining can help to provide knowledge about this disease. The knowledge extracted using Data Mining can help in treating and preventing the disease. Artificial Neural Network (ANN) can be used to create an classifier from the data. The neural network is trained using backpropagation al...

Artificial Neural Network (ANN) based model has been proposed for diagnosis of process mean shift. These are mainly generalized-based where only a single classifier was applied in the diagnosis of abnormal pattern. In this paper, we analyze the performance of a combined recognizer consisting of small-sized artificial neural networks on varying number of nodes in the hidden layer trained with Le...

Associative Models were created and used for pattern recognition tasks, but recently such models have shown good forecasting capabilities; by a preprocessing of a time series and some fit of the Model. In this paper, the Gamma Classifier is used as a novel alternative for currency exchange rate forecasting, where experimental results indicate that the proposed method can be effective in the Exc...

The authors developed an integrated computer-aided detection (CAD) scheme for detecting and classifying metaphase chromosomes as well as assessing its performance and robustness. This scheme includes an automatic metaphase-finding module and a karyotyping module and it was applied to a testing database with 200 digital microscopic images. The automatic metaphase-finding module detects analyzabl...

Good recognition accuracy can be achieved through a combination of multiple classifiers rather than a single classifier. The present paper deals with the handwritten English character recognition using multiresolution technique with Discrete Wavelet Transform (DWT) and Euclidean Distance Metric (EDM). Recognition accuracy is improved by learning rule through the Artificial Neural Network (ANN) ...