Publication: Revolutionizing Human?Computer Interaction: Unraveling the Power of Deep Learning Convolutional Neural Networks in Face Recognition
Date
2024
Authors
Baharum A.
Halamy S.
Ismail R.
Abdul Rahim E.
Mat Noor N.A.
Deris F.D.
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH
Abstract
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.
Description
Keywords
Adversarial machine learning , Contrastive Learning , Deep neural networks , Face recognition , Federated learning , Human computer interaction , Computer interaction , Convolution neural network , Convolutional neural network , Deep-learning , Facial feature , Image analyze , Image-analysis , Machine-learning , Power , Convolutional neural networks