Technologies
The first step after our prototype creation and testing was to start building the actual system. To achieve our goals and requirements we researched suitable technologies for the project.
Our project core functionalities required two database systems, one for the user login and one for the manuscripts, a responsive web-based front end solution and a deep-learning framework as back-end.
Firebase
Our database solution is Firebase. The choice was taken due to Firebase's integration and compatibility with several authentications methods. Furthermore, it allows for easy users managment from a clients standpoint.
Angular
Angular is a versitile Typescript based front-end framework. We choose this specific technology to build our web-app because of its responsive capabilities across different screensizes, speed and performance.
Tensorflow
Tensorflow is our proposed back-end solution. It offers an extensive documentation and it is considered the industry standard for machine-learning based applications. Furthermore, it offer great performance.