A Facial Recognition Method Based on Deep Residual Network against Lighting Interference
The changes under natural lighting conditions are very complex,including changes in lighting intensity,direction,color temperature,and shadows,which may have a significant impact on the appear-ance of facial images.To this end,a facial recognition method based on deep residual networks against lighting interference is proposed.A residual learning framework is introducecd,utilizing deep residual networks,to reconstruct facial images under illumination interference.Optimized white balance technology is applied to compensate for uneven lighting on the face.Convolutional neural networks are improved to achieve facial recognition,and deep learning frameworks are used to identify and verify individual identi-ties.The experimental results show that the research method can achieve facial reconstruction and has an ideal effect on facial recognition against lighting interference,with lower loss values.
deep residual networklight interferencefacial recognitionimproving convolutional neural networks
万方数据
维普
