Description: 基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。-GMM based probabilistic neural network PNN good generalization ability, the ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, and has become a solution as speaker recognition, text recognition, medical image recognition, satellite images and other real recognition when difficulties classification of very effective tool. But GMM PNN is not only the most advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other networks to other theories, such as seamless integration. Platform: |
Size: 7158 |
Author:姜正茂 |
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Description: 基于概率神经网络的数字语音识别matlab程序-probabilistic neural network based on the number of voice recognition procedures Matlab Platform: |
Size: 6891 |
Author:蒋荣 |
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Description: 基于概率神经网络的数字语音识别matlab程序-probabilistic neural network based on the number of voice recognition procedures Matlab Platform: |
Size: 9251 |
Author:刘品 |
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Description: DNA分类，包含三中模式识别经典算法的实现：K紧邻，BP神经网络，概率神经网络。-DNA classification, which includes three classic pattern recognition algorithm to achieve : K borders, BP neural networks, probabilistic neural network. Platform: |
Size: 64423 |
Author:郭瑞杰 |
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Description: DNA分类，包含三中模式识别经典算法的实现：K紧邻，BP神经网络，概率神经网络。-DNA classification, which includes three classic pattern recognition algorithm to achieve : K borders, BP neural networks, probabilistic neural network. Platform: |
Size: 192512 |
Author:郭瑞杰 |
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Description: 基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。-GMM based probabilistic neural network PNN good generalization ability, the ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, and has become a solution as speaker recognition, text recognition, medical image recognition, satellite images and other real recognition when difficulties classification of very effective tool. But GMM PNN is not only the most advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other networks to other theories, such as seamless integration. Platform: |
Size: 7168 |
Author:姜正茂 |
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Description: 基于概率神经网络的数字语音识别matlab程序-probabilistic neural network based on the number of voice recognition procedures Matlab Platform: |
Size: 7168 |
Author:蒋荣 |
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Description: 基于概率神经网络的数字语音识别matlab程序-probabilistic neural network based on the number of voice recognition procedures Matlab Platform: |
Size: 9216 |
Author:刘品 |
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Description: 概率神经网络算法的matlab实验程序 可用于车牌识别 文字识别等模式识别问题-Probabilistic neural network algorithm matlab experimental procedure can be used for license plate recognition to identify issues such as character recognition Platform: |
Size: 1024 |
Author:薛睿 |
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Description: 基于不变矩理论，提出一种应用概率神经网络作为识别器的车牌汉字识别技术。利用Pseudo-Zernike 矩特征的旋转不变性和良好
的抗噪性能，将其作为车牌汉字识别的特征矢量，结合Pseudo-Zernike 矩的快速算法和概率神经网络识别器快速学习和识别的性能，可适
应实时环境下所获取的车牌汉字灰度图像的识别，具有较高的准确率，实验结果表明了该方法的有效性。-】This paper presents a novel approach based on Pseudo-Zernike Invariant Moments(PZIM) and Probabilistic Neural Network(PNN) to
recognize license plate Chinese characters. The approach makes better use of the rotation invariant and good anti-noise performance of
Pseudo-Zernike moments and quick learning rate of PNN, and thus provides a real-time recognition of gray character images by utilizing
Pseudo-Zernike moments as feature vectors and Probabilistic Neural Network as classifier. Numeral experiment confirms that it is an effective way
to classify license plate Chinese characters. Platform: |
Size: 1236992 |
Author:ll |
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Description: 本文提出了一种新的车辆许可证盘子识别,并在此基础上提出了一种自适应图像分割方法-In this paper, a new algorithm for vehicle license
plate identification is proposed, on the basis of a novel adaptive
image segmentation technique (Sliding Windows) in
conjunction with a character recognition Neural Network. The
algorithm was tested with 2820 natural scene gray level vehicle
images of different backgrounds and ambient illumination.
The camera focused on the plate, while the angle of view and
the distance from the vehicle varied according to the
experimental setup. The license plates properly segmented
were 2719 over 2820 input images (96.4 ). The Optical
Character Recognition (OCR) system is a two layer
Probabilistic Neural Network with topology 108-180-36, whose
performance reached 97.4 . The PNN was trained to identify
multi-font alphanumeric characters from car license plates
based on data obtained from algorithmic image processing. Platform: |
Size: 831488 |
Author:keithe |
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Description: matlab环境中 关于概率神经网络源代码 注意不是关于声音识别方面的-matlab environment, probabilistic neural network source code on the note is not about the voice recognition aspects Platform: |
Size: 15360 |
Author:imella |
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Description: 结合DCT和概率神经网络进行人脸识别。先利用DCT提取特征，然后利用PNN分类，在ORL人脸库上测试效果不错。-The combination of DCT and probabilistic neural network for face recognition. First DCT Feature Extraction, and then use a PNN classification, good test results on the ORL face database. Platform: |
Size: 1024 |
Author:尹贺峰 |
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Description: Probabilistic neural network algorithm matlab experimental procedure can be used for license plate recognition to identify issues such as character recognition Platform: |
Size: 13312 |
Author:dexman |
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Description: 利用基于概率的神经网络识别算法，进行手写字体的识别。-By using the neural network recognition algorithm based on probability,recognition of handwritten font. Platform: |
Size: 344064 |
Author:dong qingxian |
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Search - probabilistic neural network recognition