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Abstract:

Facial recognition technology has become increasingly popular in various applications such as security systems, authentication processes, and social media platforms. This study focuses on implementing a system for facial recognition using deep learning techniques. The objective of this research is to explore the effectiveness of deep learning algorithms in accurately identifying and recognizing human faces. The study aims to investigate the significance of facial recognition technology, develop objectives, formulate hypotheses, and address potential limitations. A comprehensive literature review will be conducted to examine existing research and studies in the field of facial recognition using deep learning. The research methodology will involve data collection, preprocessing, model training, testing, and evaluation. The findings of the study will be discussed, and implications for future research will be presented. The study will conclude with a summary, recommendations, and conclusions for the implementation of facial recognition systems using deep learning techniques.

Table of Content:

Chapter One: Introduction
1.1 Significance of Study
1.2 Objectives of Study
1.3 Study Hypothesis
1.4 Limitation of Study

Chapter Two: Literature Review
2.1 Overview of Facial Recognition Technology
2.2 Deep Learning Techniques for Facial Recognition
2.3 Current Applications of Facial Recognition
2.4 Challenges and Limitations

Chapter Three: Research Methodology
3.1 Data Collection
3.2 Data Preprocessing
3.3 Model Training
3.4 Testing and Evaluation

Chapter Four: Discussion of Findings
4.1 Performance Evaluation of Deep Learning Algorithms
4.2 Comparison with Traditional Facial Recognition Methods
4.3 Implications for Future Research

Chapter Five: Summary, Recommendation, and Conclusion
5.1 Summary of Findings
5.2 Recommendations for Implementation
5.3 Conclusion and Final Thoughts.

Thesis Summary:

Facial recognition technology has gained significant attention in recent years due to its diverse applications in security, authentication, and social media platforms. This research focuses on implementing a system for facial recognition using deep learning techniques to enhance the accuracy and efficiency of identifying human faces. The study aims to explore the effectiveness of deep learning algorithms, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), in recognizing facial features. Through a comprehensive literature review, the study examines current research and studies in the field of facial recognition technology. The research methodology involves data collection, preprocessing, model training, testing, and evaluation to assess the performance of deep learning algorithms. The findings of the study provide insights into the potential applications and challenges of facial recognition using deep learning techniques. The study concludes with recommendations for future research and the implementation of facial recognition systems using deep learning algorithms.

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