Dissertation Topics on Facial Recognition

Covid-19 Facial Recognition Research Topics

Topic 3: An Introduction to Facial Recognition Technology

Research Aim: Facial Recognition technology is biometric software that maps the facial features of an individual mathematically and stores them as data of a face print. With the help of deep learning algorithms, the software recognizes and stores whether the image is a live capture or a digital image. Whenever an individual utilizes the software, the face is verified through the stored images in the system. If it matches the stored image, the individual is granted access. This dissertation will focus on the basics of facial recognition technology. The software will be discussed in detail. The various characteristics of the system, how it works, features it encompasses, uses, and benefits of the system, including the drawbacks, will be discussed in this research. In short, this research will be a complete guide regarding facial recognition technology.

Topic 4: How do Facial Recognition Systems Work?

Research Aim: To keep up with the latest trends and technologies, and to get the maximum benefits, we must know how a specific technology or software functions. Facial recognition systems run on an algorithm. They map a particular device, photo, ID against a person concerning its facial features.

Thus, the next time a similar image appears on the software, the face is recognised, and the user is granted access. However, the whole technology is not as easy as it sounds. This research will delve deep into how the software works through algorithms and what aspects are considered by the system.

Topic 5: Exploring High-Performance Face Detection Methods

Research Aim: Facial recognition technology employs different methods to capture and store images. These images are stored in the system for future use, and when a user uses the feature the next time, the idea is matched with the ones stored in the system.

If and when the system recognises the image, the user is granted access. The whole process includes three different methods for storing images as data. The first method is preprocessing, the second is feature extraction, and the third is classification.

The best method is determined based on technology, the system, and its utilisation. This research will explore all these three methods in detail and understand which way is chosen under which circumstance. All three forms may also be used together by the software for storing one image. Thus, all the details will be discussed in this dissertation.

Topic 6: Facial Recognition Technology in Surveillance: How Effective is it?

Research Aim: With the increasing trend of facial recognition in our everyday lives, this technology has increased in the surveillance industry. Many companies now depend on facial recognition technology to enhance their organisation’s safety.

In addition to this, this technology has also increased in homes where people have deployed facial recognition systems to ensure the safety of their living places. This research will explore in-depth how effective facial recognition is in the surveillance industry.

The study will include specific examples of how facial recognition is used for surveillance and evaluate its effectiveness.

Topic 7: Facial Recognition Algorithms: An Overview

Research Aim: Facial recognition technology relies on the use of algorithms. Without algorithms, the system cannot function. Thus, to understand the system, the algorithms must be thoroughly understood.

This research will focus on the algorithms that the system deploys to help understand how images are captured, stored, and recognized by the system to grant access to a user. These algorithms are complex in nature. Thus the research will provide the basics of it to make sure that the readers can easily understand the system.

Topic 8: The Future of Facial Recognition Technology

Research Aim: Facial Recognition is one of the most advanced technologies of the modern sciences. Many computer devices make use of this technology to enhance security as well as the user experience.

This research will discuss how this technology has successfully helped people and companies overcome their security issues, what the future holds for this technology and the benefits of implementing facial recognition.

A comparison will also be drawn with other security measures such as fingerprint and manual password entering systems. This research will provide a detailed analysis of how facial recognition technology has performed compared to other security measures and whether or not it has been successful in terms of security.

Moreover, the research will also discuss the future of this technology, how it can be improved, how and where it can be implemented, and how this system can prove to be even more beneficial for its users.

Important Notes:

As a student of facial recognition looking to get good grades, it is essential to develop new ideas and experiment with existing facial recognition theories – i.e., to add value and interest in your research topic.

Facial recognition is vast and interrelated to so many other academic disciplines like  Facebook, Instagram, Cryptocurrency, Twitter, civil engineering, facial recognition, construction, project management, engineering management, healthcare, finance and accounting, artificial intelligence, tourism, physiotherapy, sociology, management, and project management, graphic design, and nursing. That is why it is imperative to create a project management dissertation topic that is articular, sound, and actually solves a practical problem that may be rampant in the field.

We can’t stress how important it is to develop a logical research topic based on your entire research. There are several significant downfalls to getting your topic wrong; your supervisor may not be interested in working on it, the topic has no academic creditability, the research may not make logical sense, and there is a possibility that the study is not viable.

This impacts your time and efforts in writing your dissertation as you may end up in the cycle of rejection at the initial stage of the dissertation. That is why we recommend reviewing existing research to develop a topic, taking advice from your supervisor, and even asking for help in this particular stage of your dissertation.

While developing a research topic, keeping our advice in mind will allow you to pick one of the best facial recognition dissertation topics that fulfil your requirement of writing a research paper and add to the body of knowledge.

Therefore, it is recommended that when finalizing your dissertation topic, you read recently published literature to identify gaps in the research that you may help fill.

Remember- dissertation topics need to be unique, solve an identified problem, be logical, and be practically implemented. Please look at some of our sample facial recognition dissertation topics to get an idea for your own dissertation.

How to Structure your Facial Recognition Dissertation

A well-structured dissertation can help students to achieve a high overall academic grade.

• A Title Page
• Acknowledgements
• Declaration
• Abstract: A summary of the research completed
• Table of Contents
• Introduction: This chapter includes the project rationale, research background, key research aims and objectives, and the research problems. An outline of the structure of a dissertation can also be added to this chapter.
• Literature Review: This chapter presents relevant theories and frameworks by analysing published and unpublished literature available on the chosen research topic to address research questions. The purpose is to highlight and discuss the selected research area’s relative weaknesses and strengths whilst identifying any research gaps. Break down the topic, and binding terms can positively impact your dissertation and your tutor.
• Methodology: The data collection and analysis methods and techniques employed by the researcher are presented in the Methodology chapter which usually includes research design, research philosophy, research limitations, code of conduct, ethical consideration, data collection methods, and data analysis strategy.
• Findings and Analysis: Findings of the research are analysed in detail under the Findings and Analysis chapter. All key findings/results are outlined in this chapter without interpreting the data or drawing any conclusions. It can be useful to include graphs, charts, and tables in this chapter to identify meaningful trends and relationships.
• Discussion and Conclusion: The researcher presents his interpretation of the results in this chapter, and states whether the research hypothesis has been verified or not. An essential aspect of this section of the paper is to draw a linkage between the results and evidence from the literature. Recommendations with regards to implications of the findings and directions for the future may also be provided. Finally, a summary of the overall research, along with final judgments, opinions, and comments, must be included in the form of suggestions for improvement.
• References: This should be completed following your University’s requirements
• Bibliography
• Appendices: Any additional information, diagrams, and graphs used to complete the dissertation but not part of the dissertation should be included in the Appendices chapter. Essentially, the purpose is to expand the information/data.

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