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- W3123404872 abstract "The Communication plays an essential role in our daily life. People who are hearing and/or speech impaired find it difficult to communicate with others. To aid the deaf and dumb in communicating with others sign languages are used. There are many sign languages. In this paper we worked with Indian sign language. A convolutional neural network is used to identify the images and classify them. Convolutional neural network comes under deep learning algorithms. Various actions are performed in each layer of the neural network to classify the image correctly. Employing convolutional neural networks increases the accuracy of the system. The data set consists of hand gestures which are already processed and the model is trained with the dataset. The model takes hand gestures as input and converts those signs into text. Real time video feed is used as input. The model can be further trained to detect more signs depending on the efficiency of the device." @default.
- W3123404872 created "2021-02-01" @default.
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- W3123404872 date "2021-01-01" @default.
- W3123404872 modified "2023-09-27" @default.
- W3123404872 title "Indian Sign Language Recognition Using Convolutional Neural Networks" @default.
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- W3123404872 doi "https://doi.org/10.1007/978-981-15-9293-5_35" @default.
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