Description: 神经网络源码可应用于遥感图像分类，包括bp、kohonen等方法-neural network source can be used in remote sensing image classification, including bp, Kohonen methods Platform: |
Size: 4096 |
Author:刘武 |
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Description: 数据是来源于图像的不变矩提取，这里是用matlab实现的，后面可能需要用vc实现，不过也不一定，数据是由房房同学提供的，说不定不用做
利用最简单的bp神经网络来实现分类，一共两类车辆，这里是模拟实现把，识别效果还能用，先凑合着把，这里的特征提取也够玄乎。
-Data is derived from the image moment invariants extraction, this is achieved using matlab, behind vc may need to achieve, but not necessarily, the data is provided by atrial students might not need to do the simplest use of bp neural network to achieve the classification, a total of two types of vehicles, this is the realization of the simulation, also used to identify the effect, first make do with the, where feature extraction玄乎enough. Platform: |
Size: 1186816 |
Author:车林 |
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Description: 基于神经网路的遥感图像分类，使用神经网络对几幅不同频段的遥感图像分类，主要是区分图像中不同的地形区域。-Neural network-based remote sensing image classification, the use of neural networks on a number of different band remote sensing image classification, mainly to distinguish between images of different regions of the terrain. Platform: |
Size: 1244160 |
Author:xxl |
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Description: 根据：基于不变矩特征和神经网络的图像模式模糊分类 论文 在matlab上做的实验，有7个不变矩生成和神经网络分类的代码，还要论文原文-According to: Based on the characteristics of moment invariants and neural network image mode fuzzy classification papers in matlab to do the experiment, there are seven moment invariants and neural network classifier to generate the code, but also the original papers Platform: |
Size: 146432 |
Author:wanxl_xjtu |
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Description: 提出一种基于分形理论和BP 神经网络的航空遥感图像有监督分类方法。该方法尝试将航空图像
的光谱信息和纹理特征相结合。它首先将彩色航空图像由RGB 格式转化为HSI 格式,然后,根据亮度计算分
数维、多重分形广义维数谱q-D( q) 和“空隙”等基于分形的纹理特征,同时加入归一化的色度和饱和度作为光
谱特征,采用BP 神经网络作为分类器。通过对彩色航空图像的分类实验,结果证实该方法行之有效。-Based on fractal theory and BP neural network of aviation remote sensing image supervised classification method. This method tries to aerial images of the spectral information and texture characteristics of the combination. It will first color aerial images from the RGB format into HSI format, and then, according to the brightness calculation of fractal dimension, the generalized multi-fractal dimension spectrum qD (q) and the Platform: |
Size: 274432 |
Author:xuhuoping |
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Description: 基于BP神经网络的遥感图像分类代码。从样本中提取崇明岛东滩十种地物的光谱特征，并训练BP网络，再利用网络进行分类-BP neural network-based remote sensing image classification code. Extracted from samples of 10 kinds of Chongming Island, Dongtan features of the spectral characteristics and to train BP network, and then use the network to classify Platform: |
Size: 1413120 |
Author:李琛 |
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Description: 利用bp神经网络对遥感图像进行分类，输入样本值后，根据样本值对遥感图像不同的地物进行分类，分类后计算每种地物所占面积-The use of bp neural network classification of remote sensing images, enter a sample value, based on the sample value of the different features of remote sensing image classification, classification features calculated for each share of area Platform: |
Size: 3072 |
Author:sun |
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Description: matlab 神经网络算法应用于图片中人物性格识别,通过对神经网络的训练，可以识别图像中是男性还是女性-matlab neural network algorithm is applied to the picture of character recognition, neural network through training, can identify the image is male or female. . . Platform: |
Size: 638976 |
Author:Turing |
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Description: 图象处理 模式识别 多种分类方法(最临近匹配分类器、Bayes分类器、线性函数分类、非线性函数分类、神经网络分类)识别0-9数字 手写数字与数字图片,包括设计训练样品库、可以选择多种分类器来识别识别0-9这十个阿拉伯数字，包括临时手写的数字，也包括图片中的数字
-Pattern recognition image processing a variety of classification (the most close to matching classifier, Bayes classifier, a linear function of classification, non-linear function of classification, neural network classification) to identify any number of handwritten digits 0-9 and digital images, including the design of training samples library, you can choose a variety of classifier to identify the 10 Arabic numerals identify the 0-9, including temporary handwritten figures also include the number of pictures Platform: |
Size: 541696 |
Author:yao |
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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: 神经网络源码，可应用于遥感图像的分类，采用的包括bp、kohonen。可以作为范例来学习。-Neural network source code can be used in remote sensing image classification, using the included bp, kohonen. Can serve as examples to learn. Platform: |
Size: 5120 |
Author:葛宏 |
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Description: Paper on : Classification of Forest Vertical Structure in
South Korea from Aerial Orthophoto and
Lidar Data Using an Artificial Neural Network , By
Soo-Kyung Kwon, Hyung-Sup Jung * ID , Won-Kyung Baek and Daeseong Kim Platform: |
Size: 5520384 |
Author:razibaz |
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Description: 将理论知识、科学研究和工程实践有机结合起来，内容涉及数字图像处理和识别技术的方方面面，包括图像的点运算、几何变换、空域和频域滤波、小波变换、图像复原、形态学处理、图像分割以及图像特征提取的相关内容；同时对于机器视觉进行了前导性的探究，重点介绍了两种目前在工程技术领域非常流行的分类技术——人工神经网络（ANN）和支持向量机（SVM），并在人脸识别这样的热点问题中结束《精通Matlab数字图像处理与识别》。(Combining theoretical knowledge, scientific research and engineering practice, the content involves all aspects of digital image processing and recognition technology, including point operation, geometric transformation, spatial and frequency domain filtering, wavelet transform, image restoration, morphological processing, image segmentation and image feature extraction, and the exploration of the preamble of machine vision. Two kinds of classification techniques, artificial neural network (ANN) and support vector machine (SVM), which are popular in the field of engineering and technology, are introduced in this paper, and the "master Matlab digital image processing and recognition" is finished in the hot issues such as face recognition.) Platform: |
Size: 17900544 |
Author:Xingli |
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Search - neural network image classification matlab