neural network classifier
PROBABILISTIC POTENTIAL FUNCTION NEURAL NETWORK CLASSIFIER
... function neural network classifier algorithm to deal with classes which are multi-modally distributed and formed from sets of disjoint pattern clusters is proposed in the ...proposed ...
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Neural Network Classifier for Isolated Character Recognition
... RBF neural network is used for isolated character ...discuss neural network, in second section neural network classifier in isolated OCR and in next section we proposed an ...
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A faster learning neural network classifier using selective backpropagation
... a neural network classifier can learn faster, and with a greater percentage of training patterns classified ...large network problem which would benefit greatly from a reduction in training ...
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An Investigation in Sutabily of the Neural Network Classifier for Family Malware Classification
... of Neural Network Classifier algorithms despite the fact that in recent years, Neural Network Classifiers have been shown to be excellent in all ...artificial Neural ...
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Advanced E-mail Spam Detection Methodology by the Neural Network Classifier
... as Neural Network Classifier in the filtering technique to calculate the probability of Spam message from the machine learning from the Spam ...mails. Neural Network is very accurate ...
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Recognition of Multiple PQ Issues using Modified EMD and Neural Network Classifier
... Probabilistic Neural Network Classifier There are many variants of classifiers based on neural network, for instance, artificial neural network, back propagation ...
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Early Detection and Prediction of Lung Cancer Survival using Neural Network Classifier
... The early detection of lung cancer is a challenging problem, due to the structure of the cancer cells, where most of the cells are overlapped with each other. Classification is very important part of digital image ...
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Robust Neural Network Classifier
... Feed-Forward Neural Networks, M-Estimators, Classification, Robust ...Artificial Neural Networks have been successfully used in a number of applications due to their highly advantageous properties like ...
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Building and Improving Artificial Neural Network Classifier
... advanced neural networks to solve the various machine learning ...implement neural networks, like Tensorflow, Theano, PyTorch, Keras ...Artificial Neural Network ...ANN classifier using ...
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An application of artificial neural network classifier for medical diagnosis
... Artificial Neural Network (ANN), offer great advantages over conventional modelling, including the neural structure of the brain that mimics the learning capability from experiences, and the ability ...
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A Novel Neural Network Classifier for Brain Computer Interface
... Fig 1: Functional model of a BCI system In this paper, the proposed BCI system extracts features from the EEG signals using Discrete Cosine transforms. The classification of the signals is done using the Semi Partial ...
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A Neural Network Classifier Model for Forecasting Safety Behavior at Workplaces
... Bayesian network model we introduced in our previous study [16], suggesting that a Bayesian network is a more powerful classifier than ANN ...
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Wavelet based detection of ventricular arrhythmias with neural network classifier
... SciRes Copyright © 2009 Openly accessible at http://www.scirp.org/journal/JBISE/ knowledge within multi-layer networks [10]. BP per- forms the gradient descent search to reduce the mean square error between the actual ...
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Classification of Cancerous Skin using Artificial Neural Network Classifier
... Skin cancer is one kind of hazardous diseases, so it is necessary to detect early stages. In our proposed method chase approaches in which the first step is binary thresholding, and then feature extraction, and then ...
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Predicting Melting Point of Medicinal Compounds Using Neural Network Classifier
... Research Scholar 1 , Principal 2 , Dr.GRD College of Science, Coimbatore, India 1, 2 Email:[email protected] 1 , [email protected] 2 Abstract- The determination of melting point range, chemical purity and ...
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Neural network classifier for hand motion detection from EMG signal
... based neural network used by Englehart ...sponse neural network (FIRNN) ...above neural network based classification techniques may be due to quality of collected signal, signal ...
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1 Serial Neural Network Classifier for Membrane Detection using a Filter Bank.
... the network is trained on one group and tested on the remaining four ...layer network part of his method since our goal is to demonstrate the improvement achieved by the use of an ANN and ...serial ...
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Deep convolutional neural network classifier for travel patterns using binary sensors
... Vuong’s algorithm is straightforward and accurate for detecting MS travel patterns, thus we employed the algorithm to prepare the ground truth dataset for this study. Studies [11], [25] made wandering detection based on ...
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A Deep Neural Network Classifier for Decoding Human Brain Activity Based on Magnetoencephalography
... deep neural network based classifier is proposed to classify the MEG signals that were produced as the brain output for two different types of visual ...proposed classifier exhibits superior ...
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Brain Tumour Detection and Classification on Neural Network Classifier Using Random Decision Forest
... Random forest are an en masse of decision trees, each one with a different subset of the training data. The RDF is used to classify the volume of pixels (voxels) in the brain. This classifier is a supervised one, ...
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