Ocular artifact, namely eye-blink is an inevitable and one of the most destructive noises EEG signals. Many solutions detecting artifact were proposed. Different subsets features Machine Learning (ML) classifiers used for this purpose. But no comprehensive comparison these ML was presented. This paper presents twelve five classifiers, commonly in existing studies detection artifacts. An dataset...

This paper presents a thorough experimental analysis to investigate the behavior of neural network classifier for classification of multispectral satellite images. For this series of experiments have been performed to study the effect of various neural network parameters upon classification accuracy. It is per pixel supervised classification using spectral bands (original feature space). The pa...

A new approach to intelligent gas sensor (IGS) design using a classifier based on adaptive resonance theory (ART) artificial neural network (ANN) is presented. Using published data of sensor arrays fabricated and characterised at our laboratory, we demonstrate excellent gas/odour identification performance of our classifier for a 4-gas, 4-sensor system to identify individual gas/odour. Since th...

This paper describes the design and modeling of an artificial neural network (ANN) classifier using VHDL. This classifier is targeted primarily to classify the six different types of power quality disturbance. The high level architecture comprises of a control unit and a neural network datapath. The control unit is further divided into five interconnected sub modules: bus master, ram, pseudo ra...

A hybrid neural network and tree classification system for handwritten numeral recognition is proposed. The recognition system consists of coarse and fine classification based on a variety of stable and reliable global features and local features. For the coarse classifier: a four-layer feed forward neural networks with back propagation learning algorithm is employed to distinguish six subsets ...

This paper presents a thorough experimental analysis to investigate the behavior of neural network classifier for classification of multispectral satellite images. For this series of experiments have been performed to study the effect of various neural network parameters upon classification accuracy. It is per pixel supervised classification using spectral bands (original feature space). The pa...

Different data classification algorithms have been developed and applied in various areas to analyze and extract valuable information and patterns from large datasets with noise and missing values. However, none of them could consistently perform well over all datasets. To this end, ensemble methods have been suggested as the promising measures. This paper proposes a novel hybrid algorithm, whi...

We investigated the use of full-range (400–2,500 nm) hyperspectral data obtained by sampling foliar reflectances to discriminate 46 plant species in a tropical wetland in Jamaica. A total of 47 spectral variables, including derivative spectra, spectral vegetation indices, spectral position variables, normalized spectra and spectral absorption features, were used for classifying the 46 species. ...

Breast cancer is the second cause of dead among women. Early detection followed by appropriate cancer treatment can reduce the deadly risk. Medical professionals can make mistakes while identifying a disease. The help of technology such as data mining and machine learning can substantially improve the diagnosis accuracy. Artificial Neural Networks (ANN) has been widely used in intelligent breas...