Smart Face Recognition Application using Deep Learning Neural Networks with Compressed Model Deployment

This research work presents a novel face recognition system with customized face dataset. After completion of the dataset, this dataset will be fed to neural network (or) model and find how much efficient it is in detecting the student. There are different types of neural networks like ANN and its variants like CNN and RNN. For example, a person is affected by fever or cold etc. In that case, through biometric application disease the can be spread from one person to the other persons. To combat this situation, image processing authentication technique is proposed. This research study develops a new html script for accessing the camera to capture images. The input image is then fed to neural network. Here, a customized CNN model is developed. After recognition, the embedding or features of the image will be compared with the dataset. The proposed model will act like a black box, where input must be provided and it will process the image data and provide the recognized output.