• Pankaj Barde
• Aniruddha Ghadge
• Sanket Bhong
• Praful Sonawane
• Priyanka Kute

This project aims to develop an android application that can recognize hand gestures using the Kotlin programming language. The application is designed to be user-friendly and easy to use. The user can perform various hand gestures, and the application will recognize them and perform the corresponding action. The application will use the device's camera to capture the hand gestures and analyze them using machine learning algorithms. The machine learning model will be trained using a dataset of hand gestures to improve the accuracy of the recognition system. The application will have a simple and intuitive user interface that will allow the user to select the action they want to perform based on the hand gesture they make. The application will also have the option to customize the hand gestures and assign different actions to them. The Hand Gesture Recognition System Android Application will be a useful tool for people with disabilities, allowing them to control their devices using hand gestures. It will also be useful in situations where touch input is not possible, such as when the user's hands are dirty or when they are wearing gloves. Overall, this project will showcase the power of Kotlin language in developing android applications and the potential of hand gesture recognition technology in improving the user experience.

Hand-Gesture recognition, Convolutional Neural Network (CNN), Machine Learning, Sign language

"Hand Gesture Recognition System For Deaf And Dumb People", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.j225-j227, May-2023, Available :http://www.jetir.org/papers/JETIR2305982.pdf

"Hand Gesture Recognition System For Deaf And Dumb People", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppj225-j227, May-2023, Available at : http://www.jetir.org/papers/JETIR2305982.pdf