RNN-based Online Handwritten Character Recognition Using Accelerometer and Gyroscope Data

no code implementations • 24 Jul 2019 • Davit Soselia, Shota Amashukeli, Irakli Koberidze, Levan Shugliashvili

We have built a dataset of timestamped gyroscope and accelerometer data gathered during the manual process of handwriting Latin characters, labeled with the character being written; in total, the dataset con-sists of 1500 gyroscope and accelerometer data sequenc-es for 8 characters of the Latin alphabet from 6 different people, and 20 characters, each 1500 samples from Georgian alphabet from 5 different people.

Reproduction Report on "Learn to Pay Attention"

1 code implementation • 11 Dec 2018 • Levan Shugliashvili, Davit Soselia, Shota Amashukeli, Irakli Koberidze

We have successfully implemented the "Learn to Pay Attention" model of attention mechanism in convolutional neural networks, and have replicated the results of the original paper in the categories of image classification and fine-grained recognition.

General Classification Image Classification