Identification of People Based on Machine Learning Algorithm of Face Recognition

The authors of the paper considered the problem of security and recognition of objects and images using convolutional neural network. An analysis of current methods of recognizing the fragments required in the image is carried out, and studies the process of identifying faces and objects. Also, the full algorithm of the identification process is given – from building a set of databases for training the neural network to the recognition process. In addition, a comparative analysis of different methods for facial landmark detection is presented. The proposed model demonstrates high accuracy in distinguishing between masked and unmasked faces. The results have practical implications for security and monitoring systems. The study aims to optimize methods for facial and object recognition using convolutional neural networks to enhance accuracy in identifying individuals under various conditions. The methodology involves preparing a dataset, developing and training neural network models, and testing their performance under real-world scenarios, utilizing tools like TensorFlow, OpenCV, and dlib