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Evaluation of Sensor Positioning for Handwriting Recognition Through Machine Learning Techniques

Evaluation of Sensor Positioning for Handwriting Recognition Through Machine Learning Techniques
Forschungsthema:Artificial Intelligence, Embedded Systems, Prototype Development
Typ:Bachelorarbeit
Datum:offen (zu vergeben)
Betreuer:

Dr.-Ing. Tanja Harbaum

Evaluation of Sensor Positioning for Handwriting Recognition Through Machine Learning Techniques

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Background

There are numerous situations in daily life where we take notes and afterwards realize that we need the content in a digital form (like meeting notes, protocols, forms or lecture notes). But how to digitize your handwritten notes? There are different products like document scanners, tablets with a stylus or smart pens. All of these solutions require additional equipment or special paper to work correctly. With this thesis we will explore the

possibilities of improving a system that is able to digitize handwriting with a pen that writes on regular paper. Within this work there will be a strong cooperation with the STABILO International GmbH. A prototype of the DigiPen, a recording system, and a data set will be provided by STABILO.

 

Tasks

The primary goal of this thesis is the preparation and analysis of data sets of two different sensor nodes of the DigiPen. A data set comprises sensor values of a gyrometer, an accelerometer and the corresponding trajectories. The preprocessed data of both sensor nodes should be used to train a neural network and the results should be analyzed. Based on the results, the two sensor nodes should be evaluated.

 

Requirements

  • Basics of Artificial Intelligence, in particular machine-learning methods
  • First experiences with Python
  • Motivation and interest in solving technical problems independently