Abstract
Face recognition is such a problem where the accuracy is dependent on the quantity and variations of the training images. Increase of training data enhances the recognition accuracy in most cases. However, to collect and store a huge number of data in a standalone storage device is a big problem. Therefore, the researchers are being motivated towards cloud computing. Nowadays, the technology of cloud computing has made the task fairly ease even when a huge volume of data is required. This paper presents a cloud-based cohort selection approach which can be incorporated into a face recognition system. In this scheme, the cohort images as well as the training images can be accessed from the cloud servers through network connectivity. So the storage and maintenance costs are reduced whereas the accuracy is increased.
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Garain, J., Maity, S., Kumar, D. (2021). An Approach to Cohort Selection in Cloud for Face Recognition. In: Mishra, D., Buyya, R., Mohapatra, P., Patnaik, S. (eds) Intelligent and Cloud Computing. Smart Innovation, Systems and Technologies, vol 153. Springer, Singapore. https://doi.org/10.1007/978-981-15-6202-0_11
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DOI: https://doi.org/10.1007/978-981-15-6202-0_11
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