abstract-500-chars.txt 814 B

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  1. Autoren: Thoma, Martin; Kilgour, Kevin; Stüker, Sebastian; Waibel, Alexander
  2. Titel: On-line Recognition of Handwritten Mathematical Symbols
  3. Institut: Institute for Anthropomatics and Robotics
  4. Abstract (max 500 Zeichen):
  5. This paper presents a classification system which uses the pen trajectory to
  6. classify handwritten symbols. Five preprocessing steps, one data multiplication
  7. algorithm, five features and five variants for multilayer Perceptron training
  8. were evaluated using $\num{166898}$ recordings. The evaluation results of
  9. 21~experiments were used to create an optimized recognizer. This improvement
  10. was achieved by \acrlong{SLP} and adding new features.
  11. Keywords (max 5): recognition; machine learning; neural networks; symbols;
  12. multilayer perceptron
  13. Geplanter Veröffentlichungstermin: 1. August 2015