neural network recognition algorithms
REVIEW OF SPEECH AND SPEECH RECOGNITION SYSTEM USING FEATURE EXTRACTION ALGORITHM AND OPTIMIZATION ALGORITHMS
... speech recognition and speaker recognition ...speech recognition with speaker recognition based on Hidden Markov Model for security is a requirement of ...Artificial Neural networks is ...
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Scaly Neural Networks for Speech Recognition Using DTW and Time Alignment Algorithms
... alignment algorithms for preprocessing the speech pattern before it is presented to a neural network was introduced the two types of algorithm available, linear and non- linear, were ...non-linear ...
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Review of Face Recognition Systems Using Different Artificial Neural Network Algorithms
... face recognition is based on DCT (Discrete Cosine Transform) and neural ...different neural networks are used. The standard back propagation neural network is used in an „network ...
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IRIS Recognition Using Neural Network
... pre-processing algorithms that remove artifacts from the digital ...These algorithms usually enhance, segment, normalize the digital images; a feature extractor that extracts significant features; a ...
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Performance Evaluation of Neural Network and Deep Neural Network for Human Activity Recognition
... effective algorithms for HAR, 3) implementing these algorithms to infer unseen relationships on unseen data as well thus making the model generalize to recognize human activities, 4) comparing obtained ...
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A Review Paper on Currency Recognition System
... discussed recognition system of different countries like Bangladesh, China, India and recognition system for Euro ...and algorithms to develop these systems like Bangladeshi Currency ...
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FACE RECOGNITION USING GABOR WAVELET TRANSFORM AND FEED FORWARD NEURAL NETWORK
... many algorithms have been proposed as a solution to automatic face ...face recognition using Gabor wavelet transform and feed forward neural network is ...and neural network for ...
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Character Recognition Using Neural Network
... running algorithms, creating user interfaces, data visualization, and interfacing with programs developed in other languages including Java and ...with algorithms essential to required ...
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IMPLEMENTATION OF NEURAL NETWORK FOR CHARACTER RECOGNITION
... fast recognition. Although a number of good recognition algorithms have been proposed for handwritten character recognition, the achieved performance is still far from those of human beings in ...
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Neural Network and Adaptive Feature Extraction Technique for Pattern Recognition
... pattern recognition by using a neural network ...propagation neural network ...ensemble algorithms by matching the detected and the known partitions of the iris ...
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Comparison of Different Neural Network Training Algorithms with Application to Face Recognition
... All training functions have percentage of recognition above 90%. However, only small database of 400 images has been tested. Further research would include creating bigger database and testing again to see if the ...
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The Understanding of Convolutional Neuron Network Family
... Convolutional Neural Network (CNN) is one of the most popular algorithms in the field of Deep ...text recognition and other aspects of the ...Convolutional Neural Network has ...
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A Comparative Study on Various Neural Network Algorithms
... and recognition, medical imaging, speech recognition and ...Artificial Neural Networks (ANN) is a mathematical or computational model based on biological ...terms, neural networks are ...
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Putting hands to rest: efficient deep CNN-RNN architecture for chemical named entity recognition with no hand-crafted rules
... entities recognition in biomedical texts, trained and evaluated on the CHEMDNER ...entity recognition can be done efficiently with no manually created rules or curated databases ...
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The use of adversaries for optimal neural network training
... TensorFlow network was found using HyperBand [9], which narrows down the best configuration from a large random sample of hyper-parameter ...performing network is given in ...
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FACE DETECTION AND RECOGNITION USING MORPHOLOGICAL SHARED-WEIGHT NEURAL NETWORK
... experience a gradual decrease in performance, eventually hitting zero recognition at 40 neurons. As the graph in Fig. 4 indicates, efficiency increases as the number of neurons increases from 5 to 10; it remains ...
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Dynamic analysis of synchronous machine using neural network based characterization clustering and pattern recognition
... Dynamic analysis of synchronous machine using neural network Dynamic analysis of synchronous machine using neural network based characterization clustering and pattern recognition.. ba[r] ...
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Recognition of Handwritten Digit using Convolutional Neural Network in Python with Tensorflow and Comparison of Performance for Various Hidden Layers
... Convolutional Neural Networking (CNN) [1, 2] is being used for visual imagery ...face recognition, robotics, video analysis, segmentation, pattern recognition, natural language processing, spam ...
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A NOVEL TWO DIMENSIONAL SPECTRAL/SPATIAL HYBRID CODE FOR OPTICAL CODE DIVISION MULTIPLE ACCESS SYSTEM
... An ear recognition method is proposed by Revaud et al. [18], which uses the Scale-Invariant Features Transform (SIFT) method to detect features and create descriptors for them. These features are extracted for the ...
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A Radial Basis Function Approach to Retrieve Soil Moisture and Crop Variables from X-Band Scatterometer Observations
... artificial neural network ...function neural network (RBFNN) al- gorithms were used to approximate the function described by the input output relationship between the scattering coefficient and ...
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