Fig. 4From: A novel comparative deep learning framework for facial age estimationOptimization of our CRCNN approach: sensitivity of the deep architecture’s parameters. a Fusion Strategy. b Baseline. c Region detector. d CONV. Layers. e LOCAL Layers. f FULL Layers. g Batch size. h Activation function. i Dropout. j Learning rate. k Momentum. l Weight PenaltyBack to article page