rapd markers through an application of 23 decamer primers were employed for genetic diversity analysis of some sweet cherry cultivars. bands with good resolution and high repeatability were selected for evaluations. the 23 primers produced 188 bands, among which, 153 were polymorphic. cluster analysis of the cultivars was performed based on the presence (1) and absence (0) of the bands, using j...

In this paper, we design and analyze MC2G (Matrix Completion with 2 Graphs), an algorithm that performs matrix completion in the presence of social item similarity graphs. runs quasilinear time is parameter free. It based on spectral clustering local refinement steps. The expected number sampled entries required for to succeed (i.e., recover clusters graphs complete matrix) matches information-...

The original similarity measurement model is easy to ignore the processing of image details, resulting in poor accuracy measurement. In paper, we propose a for medical feature matrix based on convolutional neural network (CNN). First, Gaussian convolution kernel used obtain global and local data images, corresponding set formed. Second, layer CNN introduced, obtained by layer. Finally, construc...

In order to improve the visual effect of AR live video detail texture, an adaptive enhancement algorithm based on approximate matching is proposed. According local self-similarity original image, best block initial super-resolution image obtained. After extracting its high-frequency information, improved singular value decomposition (SVD) used embed watermark into gray image; And through extrac...

We prove that Ochiai similarity of the co-occurrence matrix is equal to cosine similarity in the underlying occurrence matrix. Neither the cosine nor the Pearson correlation should be used for the normalization of co-occurrence matrices because the similarity is then normalized twice, and therefore over-estimated; the Ochiai coefficient can be used instead. Results are shown using a small matri...

Traditional image clustering systems are primarily based on visual and/or textual features. Such algorithms commonly suffer from the problem of semantic gap. General approach to overcome this problem is to incorporate user feedback. However, data extracted from certain domains like social networks, web-blogs etc. is evolving in nature. In other words, data collected from such domains over small...

We use a cluster ensemble to determine the number of clusters, k, in a group of data. A consensus similarity matrix is formed from the ensemble using multiple algorithms and several values for k. A random walk is induced on the graph defined by the consensus matrix and the eigenvalues of the associated transition probability matrix are used to determine the number of clusters. For noisy or high...