Sensors, Vol. 20, Pages 6548: A Novel GAN-Based Synthesis Method for In-Air Handwritten Words

Sensors, Vol. 20, Pages 6548: A Novel GAN-Based Synthesis Method for In-Air Handwritten Words Sensors doi: 10.3390/s20226548 Authors: Xin Zhang Yang Xue In recent years, with the miniaturization and high energy efficiency of MEMS (micro-electro-mechanical systems), in-air handwriting technology based on inertial sensors has come to the fore. Most of the previous works have focused on character-level in-air handwriting recognition. In contrast, few works focus on word-level in-air handwriting tasks. In the field of word-level recognition, researchers have to face the problems of insufficient data and poor generalization performance of recognition methods. On one hand, the training of deep neural learning networks usually requires a particularly large dataset, but collecting data will take a lot of time and money. On the other hand, a deep recognition network trained on a small dataset can hardly recognize samples whose labels do not appear in the training set. To address these problems, we propose a two-stage synthesis method of in-air handwritten words. The proposed method includes a splicing module guided by an additional corpus and a generating module trained by adversarial learning. We carefully design the proposed network so that it can handle word sample inputs of arbitrary length and pay more attention to the details of the samples. We design multiple sets of experiments on a public dataset. The experimental results demonstrate the success of the proposed meth...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research