Outlier detection is of great significance in the domain data mining. Its task to find those target points that are not identical most object generation mechanisms. The existing algorithms mainly divided into density-based and distance-based algorithms. However, both approaches have some drawbacks. former struggles handle low-density modes, while latter cannot detect local outliers. Moreover, o...

Abstract The feature extraction of a point cloud fragment model is the basis splicing, which provides technical support for research on segmentation, and restoration surfaces. High-quality extraction, however, complicated process due to diversity surface information model. For this subject, high-efficient method was proposed address new extracting lines. First, projection distance calculated id...

The selection of a scoring matrix and gap penalty parameters continues to be an important problem in sequence alignment. We describe here an algorithm, the 'Bayes block aligner, which bypasses this requirement. Instead of requiring a fixed set of parameter settings, this algorithm returns the Bayesian posterior probability for the number of gaps and for the scoring matrices in any series of int...

Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering the importance of including spatial information of pixels which improves the quality of image segmentati...

Kernel-classifiers comprise a powerful class of non-linear decision functions for binary classification. The support vector machine is an example of a learning algorithm for kernel classifiers that singles out the consistent classifier with the largest margin, i.e. minimal real-valued output on the training sample, within the set of consistent hypotheses, the so-called version space. We suggest...

Microwave remote sensing provides an excellent means for mapping polar sea ice extent. In this study, a new algorithm for polar sea ice mapping is developed for use with the SeaWinds instrument. The approach utilizes a priori information within the framework of Bayes detection to produce sea ice extent maps. Statistical models for sea ice and ocean are represented in histograms which are filter...