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- W4313444768 abstract "Sign language is a language for communication that uses the structure of hand, facial expressions, and body language to communicate, and this is a means of communication for deaf and dumb through the use of the hands and other parts of the body. American Sign Language (ASL), which consists of static hand gestures, is one of the widely used sign languages around the world. There arises a communication barrier, when hearing people who do not understand the sign language wants to communicate with deaf and dumb people, which is a major problem in the present society. Hence, this work is focused on developing the static hand gesture recognition system, which acts as a bridge of communication between hearing people and deaf and dumb people. In the proposed work, deep learning and artificial neural network concept are used, since it provides a wide range of algorithms that can recognize objects by learning the features of the object. The proposed work is to predict the static hand gestures of ASL alphabets using Inception v3 model, which uses transfer learning to train the model." @default.
- W4313444768 created "2023-01-06" @default.
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- W4313444768 date "2023-01-01" @default.
- W4313444768 modified "2023-09-27" @default.
- W4313444768 title "Static Hand Gesture Prediction Using Inception V3" @default.
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- W4313444768 doi "https://doi.org/10.1007/978-981-19-2358-6_13" @default.
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