Abstract
In the realm of human computer interaction, sign language detection has emerged as one of the most significant study fields. Deep learning and machine learning can also be utilized to help with this problem. This may be quite useful in talking with others for the deaf and dumb. Physically challenged persons can convey their thoughts and emotions through sign language. The Indian sign language dataset has been subjected to eight machine learning approaches: SVM, Random forest, KNN, Decision tree, Logistic regression, XgBoost, LightGBM, Naïve byas and one deep learning approaches: CNN. The dataset is also subjected to pre-trained model ‘ssd_mobilnet_v2_fpnlite_320x320_coco17_tpu-8’ for real time detection of Indian sign language. Furthermore, the study intends to use comparative analysis of performance to achieve its goals to make the selection of relevant prediction techniques easier.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Engineering and Artificial Intelligence
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
