Developments in Face Recognition: A Review of Methods, Algorithms and Real- World Applications, From Classical Methods to Deep Learning
Arpana G Katti, M. V. Chidananda Murthy · 2025
The recognition of faces technology’s capacity to recognize and validate people based on their facial traits has made it an essential tool in a number of industries, including advertising safety, medical services, and communication between humans and computers. The procedure usually entails taking pictures of a person’s face, extracting pertinent traits, and then matching them to patterns that were previously recorded in order to match or identify the person. The precision and resilience of systems for recognizing faces have been substantially increased over time by notable developments in machine learning, particularly deep learning methods like convolutional neural networks. These days, these systems can deal with issues including changes in age, emotions, position, and illumination. Nevertheless, as recognizing faces grows increasingly prevalent, worries regarding security, prejudice even moral consequences keep coming up. More advancements on statistical precision improved safety protocols, and the creation of privacy- conscious structures are probably in store for the next generation of recognizing faces. Identification of faces is still a fascinating field of study with possible uses that affect vital safety mechanisms and regular life, ignoring the difficulties. A novel approach is proposed in this paper.