  We attempt to overcome the restriction of requiring a writing surface for
handwriting recognition. In this study, we design a prototype of a stylus
equipped with motion sensor, and utilizes gyroscopic and acceleration sensor
reading to perform written letter classification using various deep learning
techniques such as CNN and RNNs. We also explore various data augmentation
techniques and their effects, reaching up to 86% accuracy.
