Abstract
The present scenario in biometrics is very complex and challenging to classify the facial recognition and authentication. This article described a detailed review on machine learning. Author describes different databases and multiple approaches to overcome the issue of face identification and recognition. This paper offers a description of the work of numerous researchers on the recognition of faces and identity. It focuses on the facial recognition and recognition method in which minimal and unregulated faces processed for individual photographs, and videos are recognized and authenticated. Author describes several facial files, real-time pictures, and videos to discuss sophisticated approaches for their identification and recognition applications. The introduction of a machine learning approach with multiple image datasets also increases the efficiency of the classifier in order to predict face detection and recognition-related content. In conclusion, author elaborated the various approaches of machine learning and deep learning related to facial recognition and identification.
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Singhal, P., Srivastava, P.K., Tiwari, A.K., Shukla, R.K. (2022). A Survey: Approaches to Facial Detection and Recognition with Machine Learning Techniques. In: Gupta, D., Khanna, A., Kansal, V., Fortino, G., Hassanien, A.E. (eds) Proceedings of Second Doctoral Symposium on Computational Intelligence . Advances in Intelligent Systems and Computing, vol 1374. Springer, Singapore. https://doi.org/10.1007/978-981-16-3346-1_9
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