Neural maps project data from an input space onto a neuron position in a (often lower dimensional) output space grid in a neighborhood preserving way, with neighboring neurons in the output space responding to neighboring data points in the input space. A map-learning algorithm can achieve an optimal neighborhood preservation only, if the output space topology roughly matches the effective stru...

If the training pattern set is large, it takes a large memory and a long time to train support vector machine (SVM). Recently, we proposed neighborhood property based pattern selection algorithm (NPPS) which selects only the patterns that are likely to be near the decision boundary ahead of SVM training [Proc. of the 7th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Le...

visibility is an important factor of environmental quality that has various influences on the quality of neighborhood. this paper aimed to find the relationship between urban form and visual quality. a public space with a spatial configuration in one of bushehr city's neighborhoods was selected as the case study. bushehr city is surrounded by urban development and the sea. compact urban sp...

We explore the role of scale for improved feature learning in convolutional networks. We propose multi-neighborhood convolutional networks, designed to learn image features at different levels of detail. Utilizing nonlinear scale-space models, the proposed multineighborhood model can effectively capture fine-scale image characteristics (i.e., appearance) using a small-size neighborhood, while c...

The purpose of this research was to assess the consistency of associations between neighborhood characteristics and pregnancy-related behaviors and outcomes across four nested neighborhood boundaries using race-stratified fixed-slope random-intercept multilevel logistic models. High incivilities was associated with increased smoking, inadequate weight gain and pregnancy-induced hypertension (PI...

based on a complete heyting algebra, we modify the definition oflattice-valued fuzzifying convergence space using fuzzy inclusionorder and construct in this way a cartesian-closed category, calledthe category of $l-$ordered fuzzifying convergence spaces, in whichthe category of $l-$fuzzifying topological spaces can be embedded.in addition, two new categories are introduced, which are called the...

We built 3-D and 1-D look up tables (LUTs) to transform a user’s desired device-independent colors (CIELab) to the device-dependent color space (RGB). We considered experimental adaptive neighborhood and estimation methods for building the 3-D and 1-D LUTs. Methods of finding neighborhoods include: smallest enclosing neighborhood (SEN), smallest enclosing inclusive neighborhood (SENR), natural ...

The Kuratowski–Dugundji theorem that a metrizable space is an absolute (neighborhood) extensor in dimension n iff it is LCn−1&Cn−1 (resp., LCn−1) is extended to a class of non-metrizable absolute (neighborhood) extensors in dimension n. On this base, several facts concerning metrizable extensors are established for non-metrizable ones.