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- W4220912086 abstract "Abstract: Millions of people with speech and hearing impairments communicate with sign languages every day. For hearingimpaired people, gesture recognition is a natural way of communicating, much like voice recognition is for most people. In this study, we look at the issue of translating/converting sign language to text and propose a better solution based on machine learning techniques. We want to establish a system that hearing-impaired people may utilise in their everyday lives to promote communication and collaboration between hearing-impaired people and people who aren't trained in American Sign Language (ASL). To develop a deep learning model for the ASL dataset, we'll use a technique called Transfer Learning in combination with Data Augmentation. Keywords: Sign language, machine leaning, Transfer learning, ASL, Inception v3" @default.
- W4220912086 created "2022-04-03" @default.
- W4220912086 creator A5049975776 @default.
- W4220912086 date "2022-03-31" @default.
- W4220912086 modified "2023-10-14" @default.
- W4220912086 title "Sign Language Recognition using Deep Learning" @default.
- W4220912086 doi "https://doi.org/10.22214/ijraset.2022.40627" @default.
- W4220912086 hasPublicationYear "2022" @default.
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