Revolutionizing Human–Computer Interaction: Unraveling the Power of Deep Learning Convolutional Neural Networks in Face Recognition

• Published in: Lecture Notes in Electrical Engineering
• Main Author: Baharum A.; Halamy S.; Ismail R.; Abdul Rahim E.; Mat Noor N.A.; Deris F.D.
• Format: Conference paper
• Language: English
• Published: Springer Science and Business Media Deutschland GmbH 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204401976&doi=10.1007%2f978-981-97-2977-7_13&partnerID=40&md5=cad37c6af1910969e476168999534bf6

Face recognition, being one of the most effective applications of image analysis, has recently received a lot of attention due to the huge implication in human–computer interaction (HCI). As the availability and eligibility to detect a person’s facial features, face recognition technology has been used in biometric detection applications as uses certain aspects of a person’s physiology to identify them. In addition, Deep Learning, under the subset of machine learning, can solve various problems, especially in image processing and face recognition. The advancement and development of Deep Learning can also enhance the use of the Convolution Neural Network (CNN) as the predominant model in the field of face recognition. The paper discusses the systems based on CNN approaches and algorithms and provides a review of the CNN face recognition approach. Furthermore, each paper’s details, such as used datasets, techniques, architecture, and obtained findings, hence the application are fully summarized and analyzed. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.