Instruction

 Face recognition is a key computer vision technology that is widely used in identity verification, security monitoring, and social media. The model implementation is divided into two parts, one is the image recognition and cutting of yolo method, the other is the code part and the model implementation part. The project combines feature extraction methods such as PCA, NMF, and CNN to analyze existing schemes and propose an optimization scheme that combines traditional methods and deep learning to improve the performance and flexibility of face recognition systems 


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Week 1

   Week 1: （2025/2/2） This week, we held a panel discussion on the project and confirmed the subject model of "face recognition optimization scheme". After each member understood the scope of knowledge, relevant technology and tool resources needed to carry out the project, we identified and collected all the components needed for the project. And assign the tasks and responsibilities of each member of the project team to the project. Aim for week 1: Debugging, selection, configuration and implementation of YOLO face detection model; Develop and optimize the face recognition model, and gradually improve the recognition performance of the model Implementation of tasks: We divided the team of six into two parts. One part is responsible for debugging, selecting, getting familiar with and configuring YOLO, and the other part is responsible for optimizing the face recognition model through various tools and code. FulinYang : 1, confirmed what is YOLO face detection; 2, the benefit...
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