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Description: this is a backpropagation neural network training and testing design for two types of islamic caligraphy pattern recognition as a school project
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Size: 11264 |
Author: kim |
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Description: High information redundancy and correlation in face images result in efficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches.-High information redundancy and correlation in face images result in inefficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches.
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Size: 25600 |
Author: mhm |
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Description: Wavelet transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when Wavelet coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes Wavelet-based face recognition much more accurate than other approaches.
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Size: 21504 |
Author: mhm |
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Description: backpropagation matlab neural networks
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Size: 277504 |
Author: rado |
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Description: DigitalEyes is an OCR (Optical Character Recognizer) developed in C/Caml.
usage : ./digitaleyes[.opt] [processes in chronological order] file
-noise Reduces image noise.
-rotate Finds angle and rotate image.
-lessons Builds the lessons library.
-clessons Remove the lessons library.
-learn Takes the image and give it to the neural network which compares its output and output wanted and apply backpropagation gradient descent algorithm.
-learnall Takes all the files in learning/ directory and gives them to the neural network.
-block Detects blocks.
-init Reinitializes the Neural Network.
-o Saves current file.
-html Outputs HTML.
-nogui Do not show GTK2+ interface.
-with-threads Show GTK2+ interface with threads (default).
-no-threads Show GTK2+ interface without threads.
-help Display this list of options
--help Display this list of options
-DigitalEyes is an OCR (Optical Character Recognizer) developed in C/Caml.
usage : ./digitaleyes[.opt] [processes in chronological order] file
-noise Reduces image noise.
-rotate Finds angle and rotate image.
-lessons Builds the lessons library.
-clessons Remove the lessons library.
-learn Takes the image and give it to the neural network which compares its output and output wanted and apply backpropagation gradient descent algorithm.
-learnall Takes all the files in learning/ directory and gives them to the neural network.
-block Detects blocks.
-init Reinitializes the Neural Network.
-o Saves current file.
-html Outputs HTML.
-nogui Do not show GTK2+ interface.
-with-threads Show GTK2+ interface with threads (default).
-no-threads Show GTK2+ interface without threads.
-help Display this list of options
--help Display this list of options
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Size: 381952 |
Author: chen |
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Description: this program applying artificial intelegence with backPropagation algorithm
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Size: 130048 |
Author: buddy_boyan |
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Description: this is a .pas code for JST backpropagation, used to recognize handwritten
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Size: 528384 |
Author: reiko |
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Description: back probagation in neural network
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Size: 378880 |
Author: bashar |
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Description: ANN Backpropagation Error
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Size: 4096 |
Author: Ipoel |
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Description: backpropagation code
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Size: 57344 |
Author: malasirena |
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Description: A MLP code with backpropagation training algorithm designed for classification problems.
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Size: 1024 |
Author: Paulo |
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Description: A single perceptron code with backpropagation training algorithm designed for classification problems.
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Size: 1024 |
Author: Paulo |
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Description: MLP backpropagation xor, sin and function approximation.
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Size: 2048 |
Author: miguel |
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Description: Classify using a backpropagation recurrent network with a batch learning algorithm
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Size: 683008 |
Author: selva |
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Description: BP-神经网络 The neural network is trained with the Levenberg-Marquardt algorithm.
The activation functions can be either linear ( L ) or hyperbolic tangent ( H ).-Backpropagation neural network with one hidden layer for multivariate calibration. (Designed to model only one response y at a time)
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Size: 20480 |
Author: 郭乐 |
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Description: Backpropagation
Backpropagation is a supervised learning algorithm and is mainly used by Multi-Layer-Perceptrons to change the weights connected to the net s hidden neuron layer(s).
The backpropagation algorithm uses a computed output error to change the weight values in backward direction.
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Size: 237568 |
Author: muchizmo |
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Description: 使用BP神经网络来识别彩色图像的类. 自己取采样样本-apply the backpropagation neural network to classify a color image you choose. You need to determine the number of classes and select the
training samples by yourself.
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Size: 9216 |
Author: danny |
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Description: backpropagation algorithm program
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Size: 1024 |
Author: gousiya |
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Description: have fun with it, you can enjoy it and change everything you want, it s aal your now!!!!!
please contact me if you want ask about it by:
fauhoar@ohifaoi.com
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Size: 1024 |
Author: farid |
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Description: banana Implementacao da rede MLP canonica (backpropagation com gradiente descendente)-banana Implementacao da rede MLP canonica (backpropagation com gradiente descendente)
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Size: 31744 |
Author: gustavogrs |
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