Wenjun Zhang1, Wenfeng Wang2,3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1597-1619, 2023, DOI:10.32604/cmes.2022.020517
Abstract Face recognition has been rapidly developed and widely used. However, there is still considerable uncertainty in the
computational intelligence based on human-centric visual understanding. Emerging challenges for face recognition
are resulted from information loss. This study aims to tackle these challenges with a broad learning system (BLS).
We integrated two models, IR3C with BLS and IR3C with a triplet loss, to control the learning process. In our
experiments, we used different strategies to generate more challenging datasets and analyzed the competitiveness,
sensitivity, and practicability of the proposed two models. In the model of IR3C with BLS, the recognition rates
for… More >
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