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J-linkage 算法,可以用于多体拟合的一种策略,优于Multi-ransac-This paper tackles the problem of fitting multiple instances of a model to data corrupted by noise and outliers. The proposed solution is based on random sampling and conceptual data representation. Each point is represented with the characteristic function of the set of random models that fit the point. A tailored agglomerative clustering, called L-linkage, is used to group points belonging to the same model. The method does not require prior speci?cation of the number of models, nor it necessitate parameters tuning. Experimental results demonstrate thesuperior performances of the algorithm.
Date : 2025-12-20 Size : 269kb User : tomas

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随机产生5类二维坐标系中的数,使用SOM网络进行无监督聚类,将产生的随机数自动聚成五类,并将结果用图像直接显示出来,生成训练好的网络权值(Five kinds of random numbers in two-dimensional coordinate system are generated randomly, and unsupervised clustering is carried out using SOM network. The random numbers generated are automatically clustered into five categories, and the results are displayed directly with images to generate the trained weights of the network.)
Date : 2025-12-20 Size : 56kb User : xldtyh
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