Human Face Classification using TensorFlow and Deployment onto ASIC

Abstract

In The project aims to develop a human face classification system using TensorFlow and deploying it onto ASIC for Biometrics applications. The Convolutional Neural Networks (CNN) Algorithm is used to classify human faces into predefined categories such as age, gender, and emotion. The CNN model will be trained using a large dataset of labelled images, and the training process will be optimized for ASIC deployment. The trained model will be deployed on an ASIC chip, which is optimized for power and speed. The large dataset will be tested for accuracy and efficiency, and its performance will be evaluated in various engineering applications, such as Security, Biometrics, and Entertainment. The project will demonstrate the feasibility of using TensorFlow Lite and ASIC for developing efficient and accurate human face classification systems for Biometrics applications.