Description: This book is about the use of artificial neural networks for supervised learning problems. Many such problems occur in practical applications of artificial neural networks. For example, a neural network might be used as a component of a face recognition system for a security appli-
cation. After seeing a number of images of legitimate users' faces, the network needs to determine accurately whether a new image corresponds to the face of a legitimate user or an imposter. In other applications, such as the prediction of future price of shares on the stock exchange, we may require a neural network to model the relationship between a pattern and a real-valued quantity. Platform: |
Size: 20091030 |
Author:kj5566 |
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Description: 基于神经网络的人脸识别，效果很不错。
Neural Network-Based Face Detection-based on neural networks face recognition, the effect is pretty good. Neural Network-Based Face Detection Platform: |
Size: 1767424 |
Author:gary xu |
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Description: 基于神经元网络和 Linear Auto-Associative memory 和pca的人脸识别程序。-based on neural network and Linear Auto-Associative memory pca and face recognition procedures. Platform: |
Size: 5120 |
Author:王大宝 |
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Description: 基于人工神经网络的图像识别方法研究。基于神经网络的人脸检测研究。基于特征融合与神经网络的手写体数字识别技基于遗传神经网络的手写体数字识别研究术研究。基于遗传优化的神经网络的银行票据手写数字识别。一种改进的人工神经网络模型-Based on artificial neural network image recognition method. Neural Network Based Face Detection Research. Based on Feature Fusion and Neural Network Recognition of Handwritten Numerals Based on Genetic Neural Network Technology of handwritten numeral recognition technique research study. Optimization based on genetic neural network bank notes handwritten numeral recognition. An Improved Artificial Neural Network Model Platform: |
Size: 13884416 |
Author:cheng |
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Description: 人脸识别，基于BP神经网络的人脸图像识别方法的研究。-Face Recognition Based on BP Neural Network Face Recognition Method. Platform: |
Size: 282624 |
Author:ll |
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Description: 基于小波变换和神经网络的人脸识别：本论文围绕人脸识别问题对人脸特征提取及识别技术进行了研究。主要有：对人脸识别的研究工作进行了综述；在KL算法的基础上提出了新的基于KL的特征提取方法，克服了KL算法计算量大，计算时间长的缺点，-Based on Wavelet Transform and Neural Network Face Recognition: In this paper, issues surrounding the face recognition feature extraction and face recognition technology is studied. Mainly include: the research work on face recognition are reviewed in the KL algorithm is proposed based on the new KL-based feature extraction methods, the KL algorithm to overcome the large amount of computing time of shortcomings, Platform: |
Size: 3935232 |
Author:hyh |
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Description: 很好的关于人脸识别的毕业论文，从中国知网付费下载得到，《基于BP神经网络的人脸识别系统研究 》希望对大家有用。-About Face Recognition of good theses, pay-per-download from the Chinese HowNet be, " Based on BP Neural Network Face Recognition System" I hope useful to everyone. Platform: |
Size: 2015232 |
Author:赵洋洲 |
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Description: bp人工神经网络模式识别教程示例，研究人脸识别 手势识别有帮助-bp nervel network trainning and recognition ,e.g:face & dynamic hand gesture detection and face recognition .I hope it would be very useful for researcher ! Platform: |
Size: 44032 |
Author:于鱼 |
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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. Platform: |
Size: 25600 |
Author:mhm |
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Description: Face Recognition System Based on Different Artificial Neural Networks Models and Training Algorithms Platform: |
Size: 580608 |
Author:HansanaA |
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