In this paper, the problem of clustering data points that lie near or on a union independent low-dimensional subspaces is addressed. To end, popular spectral clustering-based algorithms usually follow two-stage strategy initially builds an affinity matrix and then applies clustering. However, inappropriate does not sufficiently connect lying same subspace will easily lead to issue over-segmenta...

We show that a Poisson cluster point process is a nearest-neighbour Markov point process 2] if the clusters have uniformly bounded diameter. It is typically not a nite-range Markov point process in the sense of Ripley and Kelly 12]. Furthermore, when the parent Poisson process is replaced by a Markov or nearest-neighbour Markov point process, the resulting cluster process is also nearest-neighb...

Five classifiers including the K-means, Fuzzy c-means, K-nearest neighbour, Multi-Layer Perceptron Neural Network and Probabilistic Neural Network classifiers are compared for application to colour grade classification and detection of bruising of Granny Smith apples. A number of suitable discriminate features are determined heuristically for the categorisation of four classes including: high g...

We have studied the S = 1/2 antiferromagnetic Heisenberg model in two dimensions, with an additional Ising next-nearest neighbour interaction. The next-nearest neighbour Ising interaction breaks the isotropy in spin space, for a ferromagnetic next-nearest neighbour interaction the system will order antiferromagnetically along the z axis. Antiferromagnetic next-nearest neighbour interactions wil...

We propose a new method for the recognition of unconstrained handwritten words consisting of Korean and numeric characters. To overcome the difficulty in separating touching characters, we adopt an oversegmentation technique and we find the optimal segment combination using a lexicon-driven word scoring technique and a nearest neighbor classifier. The optimal combination gives the final segment...

1 Singh, S. "Forecasting using a Fuzzy Nearest Neighbour Method", Proc. 6th International Conference on Fuzzy Theory and Technology , Fourth Joint Conference on Information Sciences (JCIS'98), North Carolina, vol. 1, pp.80-83, 1998 (23-28 October ,1998) ABSTRACT This paper explores a nearest neighbour pattern recognition method for time-series forecasting. A nearest neighbour method (FNNM) base...

In this paper, statistical, artificial neural networks and fuzzy based feature evaluation indices are analysed in order to determine the importance of prostate cancer prognostic markers. Seven prognostic markers are assessed in terms of 3 output classes using logistic regression as a statistical method, multilayer feedforward back propagation neural networks (MLFFBPNN) as a neural network tool,...