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首页> 外文会议>NAFOSTED Conference on Information and Computer Science >Recognize Vietnamese Sign Language Using Deep Neural Network
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Recognize Vietnamese Sign Language Using Deep Neural Network

机译：使用深神经网络认识越南手语

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摘要

World Health Organization published an article called ‘Deafness and hearing loss' in March 2020, it said that more than 466 million people in the world lost their hearing ability, and 34 million of them were children. Sign Language has been born and developed for a long time, but its application to communicate has met with many inadequacies and difficulties. Many methods of Computer Vision-based approach gave good results on Sign Language Alphabet Recognition but all of them require the perfect result from background removing step. However, when it comes to real life, removing a complex background is too difficult for any simple background removing algorithms. In this work, our main purpose is to build a model based on deep learning that can recognize Vietnamese Sign Language Alphabet in a complex environment. Results obtained show a robust accuracy of this model in recognizing Vietnamese Sign Language Alphabet.
机译：世界卫生组织于2020年3月发布了一篇名为“耳聋和听力损失”的文章，它表示，世界上有超过466万人失去了听力能力，3400万人是儿童。手语已经出生并长期开发，但其沟通的申请已经满足了许多不足和困难。基于计算机视觉的方法的许多方法对手语字母识别的良好结果得到了良好的结果，但所有这些都需要所有的背景从后台移除步骤。然而，在现实生活中，删除复杂的背景对于任何简单的背景去除算法太难了。在这项工作中，我们的主要目的是建立一个基于深度学习的模型，可以在复杂环境中识别越南手语字母表。获得的结果显示了该模型在识别越南语手语字母表中的稳健准确性。

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