Implementation of Machine Learning for Gender Detection using CNN on Raspberry Pi Platform
Gender Detection has numerous application in the field of authentication, security and surveillance systems, social platforms and social media. The proposed system describes gender detection based on Computer Vision and Machine Learning Approach using Convolutional Neural Network (CNN) which is used to extract various facial feature. First, the facial-extraction is investigated and best features are introduced which would be useful for training and testing the dataset. This learning representation is taken through the use of convolution neural network. Which reveals that the proposed system is tested across various challenging levels of face datasets and gives excellent performance efficiency of the system with gender detection rate for each of the database. This whole system is introduced by the simple and easy hardware implementation on Raspberry Pi programmed using Python.