View the published research paper on International Journals of Scientific Research for Engineering and Management from the link given: Indian Sign Language Research Paper
A Brief Intro
We are building a project that collaborates Machine Learning and Android Development with some algorithms upon the topic Indian Sign Language Detection
The project focuses on building an Easy To Use Android Application for everyone to detect the Indian Sign Language
Techniques used:
1. Machine Learning.
2. Deep Learning.
3. Data Science.
3. Android Development.
4. Graphic Designing
Technologies used
Programming Languages
1. Python 3.9.7 - A programming language for implementation of Machine Learning techniques with supportive frameworks.
2. Flutter 3.0.5 - A programming language with a backend of Dart that focuses on development of Cross Platform Android Applications.
Environments:
1. Android Studio 2.1.15 : For Android Application Development.
2. Anaconda 3.0: An environment that comes with Python Supported Python packages.
3. Jupyter Notebook: An Integrated Development Environment that runs Python scripts for Data Science and Web Scraping.
4. Visual Studio Code: For unit testing of the Pyhton Code.
Libraries and Supportive Frameworks used:
1. Pandas: A library for data preprocessing and data preparation.
2. Numpy: A library for implementation of Mathematical Computation techniques on data.
3. Matplotlib: Data Visualization framework written in Python.
4. Scikit-Learn: Implement ML algorithms and creating training and testing data.
5. Tensorflow: A high level array and tensor processing library for computation.
6. Keras: A library to create Deep Learning algorithms from scratch.
7. XGBoost: Supportive framework to implement Xtreme Boost algorithm.
8. Skimage: A library for Image Preprocessing operations.
9. Open CV Python: A high level Image Preprocessing Library.
