Cleavage classification: categorizing a vital feminine aesthetic landmark
نویسندگان
چکیده
منابع مشابه
Landmark Classification for Route Directions
In order for automated navigation systems to operate effectively, the route instructions they produce must be clear, concise and easily understood by users. In order to incorporate a landmark within a coherent sentence, it is necessary to first understand how that landmark is conceptualised by travellers — whether it is perceived as point-like, linelike or area-like. This paper investigates the...
متن کاملBiologically vital metal-based antimicrobial active mixed ligand complexes: synthesis, characterization, DNA binding and cleavage studies
Few novel cobalt(II) and copper(II) complexes [M(fmp)3]Cl2, [M(fmp)(bpy)2]Cl2,[M(fmp)(phen)2]Cl2 and [M(fmp)(phen)(bpy)]Cl2 (fmp = 3-furan-2-ylmethylene-pentane-2,4-dione, phen = 1,10-phenanthroline, bpy = 2,2'-bipyridine) have been synthesized andcharacterized by elemental analyses, molar conductance, magnetic susceptibility measurements,IR, electronic, EPR, mass spectra and cyclic voltammetri...
متن کاملSimulated Designer’s Eyes — Classification of Aesthetic Surfaces —
This paper aims to figure out difference of our impressions on curves that are used in shape designs, and also contribute industrial designers by implementing a smart computer aided design (CAD) systems which have as same feelings on curves as human designer’s. The proposed K-Vector is a mathematical form of classifying such curves by designer’s impressions.
متن کاملA new classification of resin-based aesthetic adhesive materials.
The purpose of this article is to illustrate a new classification of resin based aesthetic materials laying on the characterization of their matrix and their filler morphology. Four samples per material have been prepared for SEM evaluation. Each sample has been treated with chloroform to dissolve its matrix in order to evidence the filler morphology. A general schema of four different matrix s...
متن کاملCategorizing Children Automated Text Classification of CHILDES files
In this paper we present the application of machine learning text classification methods to two tasks: categorization of children’s speech in the CHILDES Database according to gender and age. Both tasks are binary. For age, we distinguish two age groups between the age of 1.9 and 3.0 years old. The boundary between the groups lies at the age of 2.4 which is both the mean and the median of the a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Plastic and Aesthetic Research
سال: 2016
ISSN: 2349-6150,2347-9264
DOI: 10.20517/2347-9264.2015.84