Publication

Method of analysing handwritten items

Pierre Dillenbourg, Thibault Lucien Christian Asselborn, Wafa Monia Benkaouar Johal
2021
Patents

Abstract

The present invention according to one embodiment concerns a computer-implemented method of analysing handwritten characters produced by a user. The method comprises: collecting (107) handwritten characters of the user, the user being part of a given user group; extracting (109) a set of features from the handwritten characters, and allocating a numerical value for a respective feature in the set of features, a respective feature in the set of features characterising a respective handwriting aspect; determining (111) feature specific feature mean values and feature standard deviation values for the set of features of group members of the given user group; determining (113) feature score values for the set of features, a respective feature score value depending on a respective feature value, a respective feature mean value and a respective feature standard deviation value; and determining (115) a final handwriting score for the user from the feature score values.

Official source

https://infoscience.epfl.ch/entities/publication/2518e7a5-c168-4b8d-9d9a-9f525dabcf44

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Pierre Dillenbourg, Thibault Lucien Christian Asselborn, Wafa Monia Benkaouar Johal
2021
Patents

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/2518e7a5-c168-4b8d-9d9a-9f525dabcf44

About this result

Related concepts (21)

Feature (machine learning)

In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. Choosing informative, discriminating and independent features is a crucial element of effective algorithms in pattern recognition, classification and regression. Features are usually numeric, but structural features such as strings and graphs are used in syntactic pattern recognition. The concept of "feature" is related to that of explanatory variable used in statistical techniques such as linear regression.

Euler method

In mathematics and computational science, the Euler method (also called the forward Euler method) is a first-order numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. It is the most basic explicit method for numerical integration of ordinary differential equations and is the simplest Runge–Kutta method. The Euler method is named after Leonhard Euler, who first proposed it in his book Institutionum calculi integralis (published 1768–1870).

Feature selection

Feature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Stylometry and DNA microarray analysis are two cases where feature selection is used. It should be distinguished from feature extraction. Feature selection techniques are used for several reasons: simplification of models to make them easier to interpret by researchers/users, shorter training times, to avoid the curse of dimensionality, improve data's compatibility with a learning model class, encode inherent symmetries present in the input space.

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