{'fraction_non_alphanumeric': 0.01832460732984293, 'fraction_numerical': 0.0, 'mean_word_length': 5.7105263157894735, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Health Monitoring Approaches towards Face Recognition based System

Face recognition is the most advanced technique of identification and authorization, having evolved significantly over the last ten years. Face recognition software is now widely utilized in a variety of applications, including security and other businesses. The purpose of this study is to develop a facial recognition-based automated attendance management system with active learning capabilities. To create a dependable and secure attendance tracking system, the proposed proposal employs a number of technologies. Active learning is added to address the issue of children's facial feature alterations. The technique is recommended to be used in schools, universities, businesses, and prisons.