Efficientnet Indian Sign Language Recognition Using Pretrained Weights
Keywords:
Sign language, Transfer learning, EfficientNet B0Abstract
For people who are hard of hearing, sign language is a means of communication that allows them to participate fully in society. People who are deaf or hard of hearing in India and the surrounding countries use Indian sign language (ISL). A total of thirty-five signs, including nine numerals and twenty-six alphabets, make up this sign language. It will only be understandable by people who are skilled in sign language. Because of this problem, deaf people can't communicate with hearing people in social settings. One possible solution to this problem is an automatic sign language identification system, which can help the deaf communicate better with others. This study presents a novel approach to classifying the 35 gestures used in Indian Sign Language through the application of transfer learning with the Efficient B0 model. Experimental findings from the Indian sign language (ISL) dataset were used to train the model, and it attained a 100% accuracy rate in categorizing signals in Indian sign language.
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