My name is Clare. I am a final year student studying Creative Computing. I am mainly interested in the areas of web development and artificial intelligence. I am very driven and have a passion for coding and learning new programming languages and ways to solve problems.
This project explores and understands how Convolutional Neural Networks can be used in a face recognition application. It details how machine and deep learning models are used and why CNNs are among the most popular models nowadays. Along with this, an attendance application will be developed to visualise how this will work together. Another goal of this application is to see how people feel about this type of application and the security concerns within face recognition technology.
This application will be able to predict via uploading an image and capturing a snapshot of a person’s face. It will also display the attendance to the user. The steps involved in the development were to first gather the requirements and decide which are most important, then research on machine learning and neural networks took place. After this, the model and application were designed. After the design process is complete the implementation step of the process began which included creating and choosing a model and integrating it with an application. Once all of this is complete the objective for the application is reached
The main goal of this project was to create an accurate face recognition model that could take attendance of people and integrate this into a web application. The goal of this was to create an attendance system that could improve manual attendance taking systems. Another goal of this was to explore how people feel about face recognition software, and how likely they would be to use an application that employs facial recognition. The main goals of this application were reached within the timeframe.
For this project, face recognition within attendance systems will be investigated. Through this, an application will be created to demonstrate how this will work. The central part of this project will be implementing the recognition model and how it will be made and trained to develop an accurate attendance system. Ways to improve this will be investigated, including creating accurate predictions using a small dataset using image manipulation. An essential part of this process will be researching how current image recognition models work and how elements of them can be used or studied to aid in the implementation of this project.