well-trained neural network
The Analysis Of Influence Factors Of Ito Bar’S Ideal Resistance For Multi-Finger Touch Screen
... artificial neural network (NN) is used to catch the complicated and nonlinear relationship between bar’s resistance and its relevant manufacturing ...of well-trained neural ...
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Design of Low Noise Amplifier of IRNSS using ANN
... determine neural network weights w such that the neural model output best matches the training ...A trained neural network model can then be used during microwave design ...
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Review on Classification of Genes and Biomarker Identification
... Artificial Neural Network (ANN) classifier ...(RBF) neural network for cancer classification using expression of very few ...RBF neural networked used only 9 genes for the lymphoma ...
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Title: DIABETIC RETINOPATHY DETECTION USING DEEP NEURAL NETWORK
... described neural network model based Desktop application works well for identification of Diabetic ...deep neural network architecture that is trained on thousands of images on ...
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Predicting Phishing Websites using Neural Network trained with Back Propagation
... Although a wide-range of anti-phishing solutions are offered, most of them are not talented to make a decision perfectly thus the false positive decisions rose intensely. In this section, we review current anti-phishing ...
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Learning to Recognize Animals by Watching Documentaries: Using Subtitles as Weak Supervision
... pre- trained convolutional neural network, as well as a Naive Bayes framework on a ‘bag-of-activations’ image representation, where each element of the bag is consid- ered ...how well ...
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Destructive Algorithm for Rule Extraction based on a Trained Neural Network
... nodes. The complexity problem can be alleviated by adopting heuristics to constrain the search space. The present paper introduces a new methodology for the simplification of the ANN by pruning the weights among neurons ...
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Shape Optimization of Pedestals Using Artificial Neural Network
... not well versed in these areas, shape optimization is still beyond their ...of neural network is proposed in this ...of neural network. Successfully trained network is ...
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Optimal Palette Generation Using Trained Neural Network Approach (TNN)
... self-organized neural network classifier (NNC) is used which is fed by image color values and additional local spatial ...another neural technique uses KSOM and Neural Gas Network and ...
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Using of Artificial Neural Networks to Recognize the Noisy Accidents Patterns of Nuclear Research Reactors
... Matlab's Neural Network Toolbox is software that provides comprehensive support for many proven network paradigms, as well as graphical user interfaces (GUIs) that enable to design and manage ...
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Artificial neural network trained to predict
... data obtained from the complete 3D simulations, “+” symbols are the results of the ANN predictions. at the cell end. Colors of the symbols dots and “+” are the same for the same energy..[r] ...
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Automatic Classification of Breast masses for Diagnosis of Breast Cancer in Digital Mammograms using Neural Network
... of neural network is used for classification, which is applied for two ...level, neural network classify the segmented ROI into normal (without tumor) and abnormal (with tumor) ...level ...
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Neuro PID Speed Controller for Permanent Magnet Synchronous Motor
... of neural PID speed controller of Permanent Magnet synchronous Motor ...a neural network tuned PID controller. Neural network is trained to provide the optimum value for various ...
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Local System Voting Feature for Machine Translation System Combination
... the neural network ...the neural network with one projection layer and one hidden ...the neural network are the I words produced by the I different individual sys- ...
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Artificial Neural Networks to Determine Source of Acoustic Emission and Damage Detection
... The network is generally comprised of an input, an output and one or more inside layers of ...a neural network are the adaptive adjustable parts of ...the neural network until it ...
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LI-BR Water Absorption Systems Analysis Using Artificial Neural Network (ANN)
... Artificial neural networks differ from the traditional modeling approaches in that they are trained to learn solutions rather than being programmed to model a specific problem in the normal ...once ...
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Artificial Neural Network Model for Compressive Strength of Lateritic Blocks
... best trained architecture, 3-71-1 with mix ratios inputted was used to predict the compressive strength of lateritic blocks as shown in Table ...Artificial Neural Network model for compressive ...
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DETERMINATION OF WELL EFFICIENCY USING ARTIFICIAL NEURAL NETWORK
... single well pumping test designed to investigate the performance of a pumping well under controlled variable ...pumping well is increased from an initially low constant rate through a sequence of ...
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IJCSMC, Vol. 2, Issue. 12, December 2013, pg.288 – 297 RESEARCH ARTICLE An Intelligent System for Mineral Identification using Unsupervised Learning Approach
... Abstract— KSOM is being used to identify classes of mineral in a hyperspectral data. To achieve this, Characterization map was obtained which was clustered using c-means clustering to obtain the characteristics cluster ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... of neural networks become ap- parent only for large-scale problems, which are computationally intensive and not feasible for hand ...MATLAB, neural network al- gorithms can be quickly implemented, ...
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