基于深度学习的人脸检测算法研究

Research on Face Detection Algorithm Based on Deep Learning

本文研究了基于深度学习的人脸检测方法,重点关注了YOLOv5模型。通过对YOLOv5模型进行改进,包括优化损失函数和改进网络结构,本文提高了模型的检测准确率。实验结果表明,经过150次训练后,采用的人脸检测模型在验证集上的人脸识别准确率可以达到92%。然而,实验数据集较小,对于模型的泛化能力有一定的影响,还有待进一步深入研究。

This paper studies the face detection method based on deep learning,focusing on the YOLOv5 model.By improving the YOLOv5 model,including optimizing the loss function and improving the network structure,this paper improves the detection accuracy of the model.The experimental results show that after 150 times of training,the face recognition accuracy of the adopted face detection model on the verification set can reach 92%.However,the experimental data set is small,which has a certain impact on the generalization ability of the model,and further research is needed.