Face Verification and recognition for digital forensics and information security
Budget $30-250 USD
Job Description:
Face recognition and verification is a rapidly growing field with numerous applications in digital forensics and information security. This thesis presents a study on the development of a face recognition and verification system for these areas.
First, we review the state-of-the-art in face recognition and verification techniques, including deep learning-based methods, and discuss their strengths and limitations.
Next, we present the design and implementation of our system, including data collection, feature extraction, and performance evaluation. The system utilizes a deep convolutional neural network (DCNN) for feature extraction and a support vector machine (SVM) for classification.
Experimental results show that our system outperforms traditional face recognition techniques in terms of accuracy and speed, making it a promising tool for digital forensics and information security applications.
Finally, we conclude the thesis by discussing the potential future directions and limitations of the system, as well as its potential impact on digital forensics and information security.
Project Programming Language: Python
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