Sentence examples for character classification from inspiring English sources

The process of modelling landscape tags forces researchers to confront the complexity of landscape character classification.

The method demonstrated is based on the landscape experience while walking a track and combines GIS viewshed analysis with a GIS generated landscape character classification.

Dr. McClelland, director of the Center for Mind, Brain and Computation at Stanford, said the neural processing work "led to extremely powerful systems for doing things like visual object recognition and handwritten character classification".

Machine learning techniques are also used to cleanse data in the written character classification problem.

In the detailed and strongly worded four-page letter shared with the Guardian, experts in technology law, data protection and philosophy claim that releasing more information about the volume, character and classification of removal requests would benefit the public and help inform a wider global discussion on privacy and personal data.

We chose the maximum parsimony approach in a cladistic framework because it is a character based classification method and, as such, was considered to be best adapted to meet our goals [ 35].

Altogether, none of Grandjean's main traits can be used as diagnostic character for classification of the Circumdehiscentiae, because of clear evidence for multiple parallel evolution (and in some cases also losses) of these traits.

Whereas molecular biology has permitted for most living organisms a progressive shift from character-based classifications to classifications based on genetic markers [ 5], no satisfying method for classifying phages exists at present.

The correct arrangement of the various anopheline taxa as per the traditional morphological character-based classification of anophelines was there when we considered the D3 region of 28S rRNA gene and ITS2 region of rDNA.

Ray's family system was later extended by Pierre Magnol (1638 1715) and Joseph de Tournefort (1656 1708), a student of Magnol, achieved notoriety for his botanical expeditions, his emphasis on floral characters in classification, and for reviving the idea of the genus as the basic unit of classification.

SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc. Support Vector training algorithms work with pseudocode, as well as principles of optimization, generalization and kernel theory.