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课程设计要求 0
实验一 基于模板匹配的字符识别 1
实验二 基于C均值算法的车辆检测与跟踪 3
实验三 水果分类系统设计 5
实验四 基于遗传算法的图像歪斜校准 6
实验五 基于BP网络的函数逼近 9
实验六 空调模糊控制系统设计 -Curriculum design requires 0
Experimental one based on template matching character recognition 1
C-means algorithm
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模糊C均值分类，用于图像处理中 很好用的，极力推荐 -Fuzzy C-means classification, used for image processing in a very good use, and strongly recommend
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用模糊增强的方法增加原图像的对比度，以便用于后续分类和分割-Fuzzy enhancement method of increasing the contrast of the original image, so that for subsequent classification and segmentation
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resonance imaging (MRI) data and estimation
of intensity inhomogeneities using fuzzy logic. MRI intensity
inhomogeneities can be attributed to imperfections in the
radio-frequency coils or to problems associated with the acquisition
sequences
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that arises the surface coil array.
This entropy-based method does not require classification and
robustly addresses some problems that are more severe than
those found in brain imaging, including noise, steep bias field,
sensitivity of arter
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