Japanese sign language classification based on gathered images and neural networks

This paper proposes a method to classify words in Japanese Sign Language (JSL). This approach employs a combined gathered image generation technique and a neural network with convolutional and pooling layers (CNNs). The gathered image generation generates images based on mean images. Herein, the max...

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Main Authors: Ito, Shin-ichi (Author), Ito, Momoyo (Author), Fukumi, Minoru (Author)
格式: EJournal Article
出版: Universitas Ahmad Dahlan, 2019-10-29.
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