Age And Gender Detection By Face Segmentation And Modefied CNN Algorithm

The fundamental purpose of the field of research known as “biometrics” is to explore the development of reliable approaches for identifying individuals using their observable traits. Examples of biometric identification include both physical and mental traits of an individual. As a kind of physical identification, fingerprints and facial features may be compared and analyzed. Human gait has been researched because it has the potential to be used as a behavioral identifier in computer visionUsing a Convolutional Neural Network (CNN) and a Support Vector Machine, the capacity to estimate a person's gender based on their stride was explored and investigated (SVM). Throughout our examination of CNN's potential uses for gait-based gender identification, we will strive for both a high degree of accuracy and a cheap computational cost. We analyzed and experimented with a variety of CNN architectures and hyperparameters in this setting.