Abstract

Abstract: For visually challenged people, distinguishing between different denominations of cash is a difficult process. Even though unique symbols are engraved on various currencies in India, the work is still difficult for blind individuals. The inadequacy of identifying devices prompted the development of a portable gadget for denominational segregation. This project aims to create an Android application that will assist visually and hearing-impaired people in detecting Indian cash denominations by putting a banknote in front of the camera. The work uses machine learning and Android programming approaches and is based on real-world applications. The android application uses text to speech concept to read the value of note to the user and then it converts the text value into speech. To harness the power of them all, we are leveraging the Keras, TensorFlow, Fastai, and PyTorch libraries, as well as different machine learning techniques like ResNet and MobileNet. Various technologies like machine learning models, python and many more libraries are used for the backend part of application. And for front end, java concepts and android development techniques are employed. Altogether they are integrated into a single platform which is highly user-friendly and makes it easy to use and implement in our daily life. Keywords: Denomination, Hearing-impaired, Android, Keras, TensorFlow, Fastai, PyTorch, ResNet, MobileNet

Full Text
Published version (Free)

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 call