Sign Language Detection using Deep Learning
Main Article Content
Abstract
In this paper we put forward a system that bridges the gap between people who use Sign Language to
communicate and the computer. Sign Language Recognition systems, though much crucial, suffer the lack of implementation
in our common day to day devices. This paper focuses on various techniques and tools to help resolve this gap using Deep
Learning. Here we propose a system that recognizes sign language and predicts the right sign using a web camera. The
system uses Deep learning techniques, Convolution neural networks, max pooling and ReLU activation function. We aim to
create a software which is both affordable, much more accessible to the users and works without compromising with the
desired results.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.