Abstract
The spike in challenges to security as well as information and resource management across the globe has equally borne the rising demand for a better system and technology to curb it. Despite the advancement in technology, the issues of security and information management have been lingering, due to the lack of a foolproof method of tackling it. Although widely adopted and preceding in existence, biometric systems such as fingerprint recognition have their shortcomings especially in regulating the security of public places. The use of security cameras has also been increasingly adopted especially in public places like banks, parks, airports, malls, and markets; however, it is also plagued by issues surrounding recognition and identification. A better approach might be combining the best features of the existing technologies such as foolproof verification and validation, mass identification, and instant recognition into a singular system. Although it can be considered as still in its maturing phase, face recognition technology is at the forefront of the race to tackle this global challenge. The combination of face recognition technology and artificial intelligence using deep learning might be just what the world needs to gain the leading hand and cement the challenges of security and information management in perpetuity.
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Imoh, N., Vajjhala, N.R., Rakshit, S. (2022). Experimental Face Recognition System Using Deep Learning Approaches. In: Reddy, A.B., Kiranmayee, B., Mukkamala, R.R., Srujan Raju, K. (eds) Proceedings of Second International Conference on Advances in Computer Engineering and Communication Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-7389-4_13
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DOI: https://doi.org/10.1007/978-981-16-7389-4_13
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