Publication

Abstract : In these present circumstances, the future for differently abled students is a big question mark. As the education is turning entirely toward online in which the differently abled students are the most affected ones because their principal way of learning was physical, i.e., using gestures. In this present scenario of pan-epidemic siege, the value of time cannot be ignored for the students who are progressive citizens for a better future. During this intricate time, there is a need to sustain the pace of education for every child and the most important for the differently abled children who are always more enthusiastic in taking on the challenges of life. We at this time, pledge to do our best for the rightful e-learning. In the era of technology, providing education on digital platforms, our idea is to provide some assistance in the field of education technology. The idea is to train a model which will help us to identify and classify Indian Sign Language in the most reliable way. In the previously proposed solutions, the user is restricted to have a definite background so as their model could work accurately. In our system, that limitation is withdrawn. The user can be anywhere, and yet our model would perform the most desirable. We are using OpenCV for pre-processing and a machine learning model is used to recognize hand gestures. This model can then be employed in an Android application for greater perks.