Research Area: Machine Learning
Deep Learning (DL) is becoming increasingly important in our everyday lives. Speech recognition, Cancerdiagnosis, self-driving vehicles, forecasting, and iris identification are just a few of the sectors where it has already had a big impact. Classification and pattern recognition algorithms use feature extractors that aren-t scalable for large datasets. Prior shallow networks limitations frequently prevented successful training and abstraction of hierarchical representations of multidimensional training data, but deep learning can often overcome them. The vast majority of realworld biometric systems are still unimodal. Person recognition is performed by unimodal biometric systems, which use only one source of biometric data. Problems including noisy sensor data, nonuniversality, and spoof attacks are common in such systems. Multibiometric solves these issues. This article uses a multimodal biometric system to recognise the iris, palm print, and mouth.
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Author(s) Name: J. Vasavi; M.S. Abirami
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Conferrence name: 2nd Global Conference for Advancement in Technology (GCAT)
Publisher name: IEEE
DOI: 10.1109/GCAT52182.2021.9587528
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