The Application of Artificial Intelligence and Machine Learning in Face Recognition Technology
Year: 2024
Type: article
Abstract: In the wake of the swift development of artificial intelligence (AI) and machine learning (ML) technologies, face recognition technology has emerged as a prominent research focus within the realm of biometrics. This paper delves into the most recent advancements of AI and ML algorithms with regard to enhancing the accuracy and speed of face recognition. To begin with, a comprehensive review of the development of face recognition technology is conducted. It traces the progression from traditional methods to the application of deep learning technology, while also summarizing the merits and limitations of the existing technology. Subsequently, the key technologies used in this paper are elaborated upon in meticulous These encompass the convolutional neural network (CNN), deep learning feature extraction, transfer learning, and the attention mechanism in face recognition, among others. These markedly augment the model's processing capabilities when dealing with complex scenes, varying lighting conditions, and occlusion situations. Furthermore, this paper undertakes an exploration of privacy protection and ethical concerns, It puts forward strategies aimed at bolstering data protection and privacy security without compromising the identification performance. Finally, the principal findings of this study are encapsulated, and future research directions are outlined. These include the further optimization of algorithms to curtail the consumption of computing resources, the development of more efficient data enhancement techniques to enhance model generalization, and exploration of a broader range of application scenarios, such as intelligent security, personalized services, and accessibility assistance systems. This study not only provides theoretical underpinning and practical guidance for the development of face recognition technology but also paves the way for promoting the extensive application of AI technology in social life.
Author: Zhonghao Li
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4405590349