TY - JOUR ID - 80022 TI - Comparative Analysis of Machine Learning Based Approaches for Face Detection and Recognition JO - Journal of Information Technology Management JA - JITM LA - en SN - AU - Kumar Shukla, Ratnesh AU - Kumar Tiwari, Arvind AD - Ph.D. Candidate, Department of Computer Science & Engineering, Dr. APJ Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India. AD - Associate Professor, Department of Computer Science & Engineering, Kamla Nehru Institute of Technology, Sultanpur, Uttar Pradesh, India. Y1 - 2021 PY - 2021 VL - 13 IS - 1 SP - 1 EP - 21 KW - Biometric machine KW - Convolution neural network KW - Deep Neural Network KW - Facial action unit KW - Random convolution neural network etc DO - 10.22059/jitm.2021.80022 N2 - This article discusses a device focused on images that enables users to recognise and detect many face-related features using the webcam. In this article, we are performing comprehensive and systemic studies to check the efficacy of these classic representation learning structures on class-imbalanced outcomes. We also show that deeper discrimination can be learned by creating a deep network that retains inter-cluster differences both and within groups. MobileNet, which provides both offline and real-time precision and speed to provide fast and consistent stable results, is the recently suggested Convolutional Neural network (CNN) model. The recently proposed Convolutional Neural Network (CNN) model is MobileNet, which has both offline and real-time accuracy and speed to provide fast and predictable real-time results. This also solved a problem related to the face that occurs in the identification and recognition of the face. This paper presents the different methods and models used by numerous researchers in literature to solve the issue of faces. They get a better result in using the highest number of layers. It is also noted that the combination of a machine learning approach with multiple image-based dataset increases the efficiency of the classifier to predict knowledge related to face detection and recognition UR - https://jitm.ut.ac.ir/article_80022.html L1 - https://jitm.ut.ac.ir/article_80022_4a3a49b492178f2ad40426ac2f6dba45.pdf ER -