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...
Week 2: (2025/2/9) This week, through division of labor and collaboration, we have completed the preliminary coding of the YOLO v11 model, and the model can more accurately identify and segment objects in images. Aim for week 2: Debugging, configuration and implementation of YOLO face detection model; Develop and optimize the face recognition model, and gradually improve the recognition performance of the model; Introduce automated scripts Implementation of tasks: Siqi Jia, Jinrun Tan: 1. Introduce automated scripts to handle the time-consuming processing of documents in multiple language versions to ensure consistency and accuracy of the documents. 2. Test model export, confirm callback information, and export functionality is normal. 3. Detect image segmentation effects and use segmentation models to train COCO segmentation datasets FulinYang : 1. The method of early stopping and learning rate self modification was used to reduce the overfitting of the YOLO V11 model. 2. ...
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