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Aggarwal, Aayush (2023) American Sign Language Recognition using Computer Vision and Deep Learning. Masters thesis, Dublin, National College of Ireland.
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Abstract
Sign language recognition system helps to understand the hand gestures made by speech and hearing-impaired community that involves movement of fingers and different palm orientations. This framework has experienced significant growth in the field of computer vision and deep learning. The researcher has investigated various hardware and software approaches for accurate sign recognition. American sign language dataset was used to achieve the goal of this study. The author has performed exploratory data analysis to get insights into data and applied preprocessing techniques such as image resizing, smoothing, and re-scaling. Two deep learning models were implemented for this research, namely Convolutional Neural Network (CNN) and Residual Network 50 (ResNet50). A 2D CNN which consists of optimized hyper-parameters outperformed the other model and achieved an accuracy of 98.76%. A learning curve was also demonstrated for accuracy and loss which was considered during model evaluation.
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