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neural network fusion method

A Deep Neural Information Fusion Architecture for Textual Network Embeddings

A Deep Neural Information Fusion Architecture for Textual Network Embeddings

... proposed method outperforms baseline methods ...the network embeddings gener- ated by the proposed model are easier to pre- serve the original information in the ...proposed fusion method and ...

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Method of Wireless Sensor Network Data Fusion

Method of Wireless Sensor Network Data Fusion

... data fusion method based on wireless sensor networks is de- ...RBF neural networks, a heterogeneous RBF neural network information fusion algo- rithm in wireless sensor networks ...

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Curvelet and Wavelet Image Fusion using          Neural Network Algorithm

Curvelet and Wavelet Image Fusion using Neural Network Algorithm

... image fusion, Seismic exploration, Turbulence analysis in fluid mechanics and so ...this method can manage the vagueness and ambiguity in many image reconstruction applications ...

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Curvelet Image Fusion using Neural Network and SVM Algorithm

Curvelet Image Fusion using Neural Network and SVM Algorithm

... image fusion process which is suitable for pan-sharpening of multispectral (MS) groups furthermore in view of multi-resolution ...image fusion strategy gives high quality of the spectral content of the ...

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A Time-Frequency Feature Fusion Algorithm Based on Neural Network for HRRP

A Time-Frequency Feature Fusion Algorithm Based on Neural Network for HRRP

... feature fusion method and single ...multi-layer neural network as a ...perform fusion, we do not use convolution layer and pooling ...fully-connected neural network with ...

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Speaker adapted neural network based fusion for multimodal reference resolution

Speaker adapted neural network based fusion for multimodal reference resolution

... early fusion, and the decision is ob- tained using a ...Their method computed linguistic, gaze and task- specific features for each object of the board game and the objects were ranked using an SVM clas- ...

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Deep Reinforcement Learning of the Model Fusion with Double Q learning

Deep Reinforcement Learning of the Model Fusion with Double Q learning

... the network, we call it the neural network of the model ...the neural network is trained, the hypothesis is independent and ...the neural network is ...this method ...

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Multi Modal Iris Recognition System based on Convolution Neural Network

Multi Modal Iris Recognition System based on Convolution Neural Network

... convolutional neural network and softmax classifier is used for multi-class ...level fusion method is used to fuse right and left iris in order to improve the confidence level of ...This ...

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A Gesture Recognition Method Integrating RGB and Depth Image Features

A Gesture Recognition Method Integrating RGB and Depth Image Features

... convolutional neural network, it is often performed in a single ...channel network, the input image often has grayscale, color, and depth ...convolutional neural networks, the article [7] uses ...

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A novel 
		approach for fusion of panchromatic and multispectral image through 
		neural network

A novel approach for fusion of panchromatic and multispectral image through neural network

... image fusion includes imaging, computer vision, remote sensing and microscopic imaging ...satellite method, gather panchromatic images at high resolution and multispectral images at low ...

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Text Dependent Speaker Recognition using MFCC features and BPANN

Text Dependent Speaker Recognition using MFCC features and BPANN

... recognition method uses phoneme context information and hence high recognition accuracy is easily ...recognition method does not require specially designed utterances and hence is user ...

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A New Localization Algorithm for Underwater Acoustic Sensor Networks

A New Localization Algorithm for Underwater Acoustic Sensor Networks

... simple method to synchronize is to use the time difference between the two miscellaneous signal entrances; the two signals having different flux speed are released at the same ...AOA method need the anchor ...

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APPLICATION OF ARTIFICIAL NEURAL NETWORK IN OPTIMIZATION OF SOAP PRODUCTION

APPLICATION OF ARTIFICIAL NEURAL NETWORK IN OPTIMIZATION OF SOAP PRODUCTION

... the neural network for training, the data had to be arranged in the form of input variables and output ...the network. The number of neurons used for the training of the network was set at 50 ...

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Oil Price Forecasting Based on EMD and BP AdaBoost Neural Network

Oil Price Forecasting Based on EMD and BP AdaBoost Neural Network

... (EMD) method in 1998; it is in a position to smooth nonlinear, non-stationary raw time series data signals while maintaining the originality as much as possible in the decomposi- tion ...artificial neural ...

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Artificial Neural Network Control of Permanent Magnet Synchronous Motor

Artificial Neural Network Control of Permanent Magnet Synchronous Motor

... A PMSM parameter estimation strategy is introduced here with the use of a feed-forward neural network. The design of high-performance control system generally requires the use of adaptive control techniques ...

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A NOVEL TWO DIMENSIONAL SPECTRAL/SPATIAL HYBRID CODE FOR OPTICAL CODE DIVISION 
MULTIPLE ACCESS SYSTEM

A NOVEL TWO DIMENSIONAL SPECTRAL/SPATIAL HYBRID CODE FOR OPTICAL CODE DIVISION MULTIPLE ACCESS SYSTEM

... recognition method is proposed by Revaud et ...(SIFT) method to detect features and create descriptors for ...convolutional neural network is used to match these descriptors, ...SIFT ...

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Probability method of reliability for cooperative neural network

Probability method of reliability for cooperative neural network

... cooperative neural network, deterministic method of neural network design involves the selection of design loadings which are unlikely to be exceeded, together with a low competence of ...

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Ionospheric Tomography by Neural Network Collocation Method

Ionospheric Tomography by Neural Network Collocation Method

... multi-layer neural network is trained for a set of combinations of an input dataset (a “pattern”) and a known output dataset (a “teacher dataset”) by minimizing an object function (a sum of squared di ff ...

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Online Failure Prediction for Railway Transportation System based on Fuzzy Rules and Data Analytics

Online Failure Prediction for Railway Transportation System based on Fuzzy Rules and Data Analytics

... Berenji et al use Gaussian rules, a so-called diagnostic model, to compute a diagnostic signal, whose value ranges from 0 (fault free) to 1 (faulty), based on the input and output data of components. The rule base is ...

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Adaptive Neural Network Tracking Control for a Class of SISO Affine Nonlinear Uncertain Systems

Adaptive Neural Network Tracking Control for a Class of SISO Affine Nonlinear Uncertain Systems

... new neural network adaptive control method for a class of SISO affine nonlinear uncertain ...adaptive neural network control term with its adaptive law, and no robustifying control term ...

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