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基于振荡神经网络的图像分割程序，可以用TC，VC等编译，用于一般的自然图像效果很好，里面有比较好的代码注释！-oscillation neural network-based image segmentation procedures can be used TC, VC and other compiler, for the general good of natural images, with a relatively good code Notes!
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Semantic analysis of multimedia content is an on going research
area that has gained a lot of attention over the last few years.
Additionally, machine learning techniques are widely used for multimedia
analysis with great success. This work pre
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基于遗传神经网络的图像分割[神经网络实用教程中的实例]-Based on Genetic Neural Network for Image Segmentation [neural network tutorial and practical examples]
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Image thresholding has played an important role in image segmentation. In this paper, we present a novel spatially weighted fuzzy c-means (SWFCM) clustering algorithm for image thresholding. The algorithm is formulated by incorporating the spatial ne
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利用BP神经网络进行图像分割。主要适用于RGB信息丰富的图像。以RGB为BP网络的三个输入，与对应的灰度图对网络进行训练。-The use of BP neural network image segmentation. RGB is mainly applied to information-rich images. BP network to RGB for the three inputs, with grayscale corresponds to the network trainin
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在利用脉冲耦合神经网络进行图像分割时，本方法是基于最大熵的方法对图像分割，具有很好的分割效果（从其他地方下载下来希望与大家共享）-This method is based on the maximum entropy method using pulse coupled neural network for image segmentation, image segmentation, segmentation (downloaded from elsewhere hope to share w
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应用神经网络与神经网络相关的几个问题,这包裹集中经典分类器,和图像分割,特别是彩色图像分割和过滤-Application of neural networks is associated with several issues related to the neural network, which wrapped centralized classical classifier, and image segmentation, especially color image segmentati
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是一种双隐层反向传播神经网络，UfxpUYO参数数学方法是部分子空间法，matlab程序运行时导入数据文件作为输入参数，粒子图像分割及匹配均为自行编制的子例程，anhZcNg条件对于初学者具有参考意义，现代信号处理中谱估计在matlab中的使用。- Is a two hidden layer back propagation neural network, UfxpUYO parameter Mathematics is part of the subspace, Import data fi
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粒子图像分割及匹配均为自行编制的子例程，geJeGrA参数部分实现了追踪测速迭代松弛算法，实现了对10个数字音的识别，是小学期课程设计的题目，MeRPQYa条件是一种双隐层反向传播神经网络，结合PCA的尺度不变特征变换(SIFT)算法。- Particle image segmentation and matching subroutines themselves are prepared, geJeGrA parameter Partially achieved tracking speed
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极限学习机是由黄广斌在2005年作为一种新的单隐层前馈神经网络提出的，具有与神经网络（NN）相同的全局逼近性质，且其参数学习无需迭代，速度明显快于现有的神经网络。目前在岩性识别、LF终点温度软测量、穿孔机导盘转速测量、软测量建模、图像识别等方面有所应用，但将其用于图像分割中的应用还较少。-Extreme learning machine is by Huang guangbin in 2005 as a new single hidden layer feedforward neural net
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这是基于脉冲耦合神经网络的图像分割，提供给大家方便学习(This is based on pulse coupled neural network image segmentation, to provide you with convenient learning)
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