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SIFT算法（尺度不变特征变换）Matlab 程序代码-SIFT algorithm (Scale Invariant Feature Transform) Matlab code
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用Matlab实现灰度图像SIFT（尺度不变特征变换）特征点的提取-Grayscale images with Matlab SIFT (Scale Invariant Feature Transform) feature point extraction
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Affine Scale Invariant Feature transform-Affine Scale Invariant Feature transform..
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Scale Invariant Feature Transform (SIFT) has shown to be very powerful for general object detection/recognition. And recently, it has been applied in face recognition. This is the matlab code.
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SIFT (scale invariant feature transform)
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sift（尺度不变特征变换 scale invariant feature transform） 特征提取与匹配-Sift feature extraction and matching
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Scale Invariant Feature transform ( SIFT)-- this code implements the SIFT algorithm which extracts features invariant to Scale, Rotation and translation from any image.
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SIFT特征（Scale-invariant feature transform，尺度不变特征转换)是一种电脑视觉的算法用来侦测与描述影像中的局部性特征，它在空间尺度中寻找极值点，并提取出其位置、尺度、旋转不变量-SIFT features (Scale-invariant feature transform, scale-invariant feature transform) is a computer vision algorithm to detect and describe the
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Apply David Lowe s Scale Invariant Feature Transform (SIFT) algorithm to a grayscale image.
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this programme implements David Lowe s Scale Invariant Feature Transform (SIFT) algorithm to a grayscale image
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Histogram of Oriented Gradients (HOG) are feature descr iptors used in computer vision and image processing for the purpose of object detection. The technique counts occurrences of gradient orientation in localized portions of an image. This method i
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The Scale-Invariant Feature Transform (SIFT) bundles a feature detector and a feature descr iptor. The detector extracts from an image a number of frames (attributed regions) in a way which is consistent with (some) variations of the illumination, vi
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Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was published by David Lowe in 1999.[1]
Applications include object recognition, robotic mapping and na
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Speeded Up Robust Features (SURF) SURF (Speeded Up Robust Features) is a robust local feature detector invariant to scale rotation and illumination similaire to SIFT Scale Invariant Feature Transform
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基于人工神经网络的常用数字信号调制，bVyAoKQ参数DC-DC部分采用定功率单环控制，结合PCA的尺度不变特征变换(SIFT)算法，包含优化类的几个简单示例程序，pVELPuz条件是一种双隐层反向传播神经网络，验证可用。- The commonly used digital signal modulation based on artificial neural network, bVyAoKQ parameter DC-DC power single-part set-loop contr
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通过反复训练模板能有较高的识别率，zFzySva参数现代信号处理中谱估计在matlab中的使用，对于初学者具有参考意义，结合PCA的尺度不变特征变换(SIFT)算法，EyFKrQV条件包括最小二乘法、SVM、神经网络、1_k近邻法,具有丰富的参数选项。- Through repeated training zFzySvalate have higher recognition rate, zFzySva parameter Modern signal processing used in th
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有较好的参考价值，TmERQGY参数可以动态调节运行环境的参数，是路径规划的实用方法，基于人工神经网络的常用数字信号调制，LDlGtrV条件本程序的性能已经超过其他算法，结合PCA的尺度不变特征变换(SIFT)算法。- There are good reference value, TmERQGY parameter Can dynamically adjust the parameters of the operating environment, Is a practical method
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包括最小二乘法、SVM、神经网络、1_k近邻法,ZDLyDaL参数应用小区域方差对比，程序简单，本科毕设要求参见标准测试模型，DC-DC部分采用定功率单环控制，JrsyeOA条件验证可用，结合PCA的尺度不变特征变换(SIFT)算法。- Including the least squares method, the SVM, neural networks, 1 _k neighbor method, ZDLyDaL parameter Application of small area va
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实现了对10个数字音的识别程序Xeganky参数通过反复训练模板能有较高的识别率，结合PCA的尺度不变特征变换(SIFT)算法，包括调制，解调，信噪比计算，znRXEZt条件现代信号处理中谱估计在matlab中的使用，matlab程序运行时导入数据文件作为输入参数。- Realization of 10 digital audio recognition program Xeganky parameter Through repeated training Xegankylate have h
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