论文标题
基于在线大写字母的自动性别识别的初步实验
Preliminary experiments on automatic gender recognition based on online capital letters
论文作者
论文摘要
在本文中，我们提供了一些实验，以根据大写字母自动对在线手写文本进行分类。尽管手写文本不像面部或声音那样歧视，但我们仍然为基于手写文本的性别分类找到了一些机会。即使在最具挑战性的大写字母案例中，精度也高达74％。
In this paper we present some experiments to automatically classify online handwritten text based on capital letters. Although handwritten text is not as discriminative as face or voice, we still found some chance for gender classification based on handwritten text. Accuracies are up to 74%, even in the most challenging case of capital letters.
