Autoren: Thoma, Martin; Kilgour, Kevin; Stüker, Sebastian; Waibel, Alexander
Titel: On-line Recognition of Handwritten Mathematical Symbols
Institut: Institute for Anthropomatics and Robotics

Abstract (max 500 Zeichen):
This paper presents a classification system which uses the pen trajectory to
classify handwritten symbols. Five preprocessing steps, one data multiplication
algorithm, five features and five variants for multilayer Perceptron training
were evaluated using $\num{166898}$ recordings. The evaluation results of
21~experiments were used to create an optimized recognizer. This improvement
was achieved by \acrlong{SLP} and adding new features.

Keywords (max 5): recognition; machine learning; neural networks; symbols;
multilayer perceptron

Geplanter Veröffentlichungstermin: 1. August 2015