Search results for "Centroid"
showing 10 items of 37 documents
1-(Pyridin-4-yl)-3-(2,4,6-trichlorophenyl)benz[4,5]imidazo[1,2-d][1,2,4]triazin-4(3H)-one
2016
In the title compound, C20H10Cl3N5O, the 13-membered ring system makes dihedral angles of 78.64 (9)° with the trichlorophenyl ring and 62.60 (10)° with the pyridine ring. The crystal packing is dominated by π–π interactions between the 13-membered ring systems [centroid–centroid distance = 3.6655 (11)°].
Objective measurement of intraocular forward light scatter using Hartmann-Shack spot patterns from clinical aberrometers. Model-eye and human-eye stu…
2007
Purpose To apply software-based image-analysis tools to objectively determine intraocular scatter determined from clinically derived Hartmann-Shack patterns. Setting Aston Academy of Life Sciences, Aston University, Birmingham, United Kingdom, and Department of Optics, University of Valencia, Valencia, Spain. Methods Purpose-designed image-analysis software was used to quantify scatter from centroid patterns obtained using a clinical Hartmann-Shack analyzer (WASCA, Zeiss/Meditec). Three scatter values, as the maximum standard deviation within a lenslet for all lenslets in the pattern, were obtained in 6 model eyes and 10 human eyes. In the model-eye sample, patterns were obtained in 4 sessi…
Machine learning for rapid mapping of archaeological structures made of dry stones – Example of burial monuments from the Khirgisuur culture, Mongoli…
2020
11 pages; International audience; The present study proposes a workflow to extract from orthomosaics the enormous amount of dry stones used by past societies to construct funeral complexes in the Mongolian steppes. Several different machine learning algorithms for binary pixel classification (i.e. stone vs non-stone) were evaluated. Input features were extracted from high-resolution orthomosaics and digital elevation models (both derived from aerial imaging). Comparative analysis used two colour spaces (RGB and HSV), texture features (contrast, homogeneity and entropy raster maps), and the topographic position index, combined with nine supervised learning algorithms (nearest centroid, naive…
Pattern classification using a new border identification paradigm: The nearest border technique
2015
Abstract There are many paradigms for pattern classification such as the optimal Bayesian, kernel-based methods, inter-class border identification schemes, nearest neighbor methods, nearest centroid methods, among others. As opposed to these, this paper pioneers a new paradigm, which we shall refer to as the nearest border (NB) paradigm. The philosophy for developing such a NB strategy is as follows: given the training data set for each class, we shall attempt to create borders for each individual class. However, unlike the traditional border identification (BI) methods, we do not undertake this by using inter-class criteria; rather, we attempt to obtain the border for a specific class in t…
A new paradigm for pattern classification: Nearest Border Techniques
2013
Published version of a chapter in the book: AI 2013: Advances in Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-03680-9_44 There are many paradigms for pattern classification. As opposed to these, this paper introduces a paradigm that has not been reported in the literature earlier, which we shall refer to as the Nearest Border (NB) paradigm. The philosophy for developing such a NB strategy is as follows: Given the training data set for each class, we shall first attempt to create borders for each individual class. After that, we advocate that testing is accomplished by assigning the test sample to the class whose border it lies closest to…
Editing prototypes in the finite sample size case using alternative neighborhoods
1998
The recently introduced concept of Nearest Centroid Neighborhood is applied to discard outliers and prototypes 111 class overlapping regions in order to improve the performance of the Nearest Neighbor rule through an editing procedure, This approach is related to graph based editing algorithms which also define alternative neighborhoods in terms of geornetric relations, Classical editing algorithms are compared to these alternative editing schemes using several synthetic and real data problems. The empirical results show that, the proposed editing algorithm constitutes a good trade-off among performance and computational burden.
Experimental validation for spectrum cartography using adaptive multi-kernels
2017
This paper validates the functionality of an algorithm for spectrum cartography, generating a radio environment map (REM) using adaptive radial basis functions (RBF) based on a limited number of measurements. The power at all locations is estimated as a linear combination of different RBFs without assuming any prior information about either power spectral densities (PSD) of the transmitters or their locations. The RBFs are represented as centroids at optimized locations, using machine learning to jointly optimize their positions, weights and Gaussian decaying parameters. Optimization is performed using expectation maximization with a least squares loss function and a quadratic regularizer. …
Improving the k-NCN classification rule through heuristic modifications
1998
Abstract This paper presents an empirical investigation of the recently proposed k-Nearest Centroid Neighbours ( k -NCN) classification rule along with two heuristic modifications of it. These alternatives make use of both proximity and geometrical distribution of the prototypes in the training set in order to estimate the class label of a given sample. The experimental results show that both alternatives give significantly better classification rates than the k -Nearest Neighbours rule, basically due to the properties of the plain k -NCN technique.
MORPHOMETRIC ANALYSIS OF HUMAN CORNEAL ENDOTHELIUM BY MEANS OF SPATIAL POINT PATTERNS
2002
This paper presents a method for detecting abnormalities in spatial arrangements of cells within any tissue that can be described by different sets of relevant points. The method has been applied to the detection of subtle abnormalities in corneal endothelia. Images of this type of tissue can be characterized by two types of points: cell centroids and triple points associated with the apical intersections as it was proposed by Díaz.7 Both types of points jointly considered are modeled using a bivariate spatial point process; then a statistical analysis based on certain distributional descriptors proposed by Doguwa4,9 is carried out to discriminate severe and subtle abnormalities from contr…
Measuring the Spatial Homogeneity in Corneal Endotheliums by Means of a Randomization Test
1999
Quantification of regularity of cell sizes and the spatial arrangement of cells in corneal endotheliums becomes of a great importance associated to stress situations such as cataract surgery, corneal transplantation or implantation of intra-ocular lenses. A new index of regularity of the spatial distribution of cell sizes in corneal endotheliums is proposed. The corneal endothelium is described by means of a spatial marked point pattern (the cell centroids marked with the cell areas). The hypothesis of no dependency between mark and locations is tested by a Monte Carlo test. The new index is the p-value of the test validating the hypothesis. Pairs of endotheliums from different eyes of the …