Face Biometric Prediction and cyber-attacks experienced Using Deep Learning Model

Identify the Face biometric prediction by using digital image processing techniques as well as deep learning model. So we introduce image processing and deep learning technique to determine face at initial stage. Initially, the source images are collected from by using the U-Net based technique. And also extract the features from input image. Finally, classify the images as diseases affected or healthy as classify by using Deep Convolution Generative Adversarial Network (DCGAN). In this proposed model, experimentation is conducted using the python Open CV model, and the performance is evaluated using different performance measures, which is designated in the result section. During the feature extraction process, the threshold values are also dynamically modified. The CNN's advantage is clear because of the uncertainty caused by noise. In the proposed method, 97.94 percent of the data was correctly classified.