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In this paper research on a compact deep convolutional neural network (DCNN) architecture for age and gender estimation from facial images has been presented. The proposed solution was tested on the FERET and the Adience Benchmark databases. In the first case a 98.6% accuracy for gender and 86.4% for age estimation was obtained. For the Adience database, which contains images recorded in unconstrained...
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