This repository contains the project developed for CSE535: Mobile Computing, representing a sophisticated Android application designed for recognizing handwritten digits. The app integrates a cutting-edge machine learning model and employs a peer-to-peer computing approach, incorporating a master-slave architecture, to ensure precise digit recognition.
- 🖊 Handwritten Digit Recognition:
- Implements advanced machine learning models for accurate recognition of handwritten digits.
- 🤖 Peer-to-Peer Computing:
- Employs a robust master-slave architecture to enable efficient computing between peers.
- 🛠 Technologically Advanced:
- Developed using Java in the Android Studio environment, adhering to optimal coding practices and standards.
- Programming Language: Java
- Development Environment: Android Studio
- Computing Architecture: Peer-to-Peer (Master-Slave)
This application is a dedicated endeavor under the CSE535: Mobile Computing course, aiming to delve deep into the exploration and implementation of diverse mobile computing paradigms and applications.
Refer to the installation instructions encapsulated in the installation guide to configure the app on your Android device and navigate through its extensive functionalities.
Feel encouraged to fork this project, contribute, and initiate pull requests for enhancing the application or extending its feature set. For reporting issues or suggesting enhancements, please utilize the issue tracker.
🙏 Thank you for exploring this Mobile Computing Project!