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In this paper we propose an implement a general convolutional neural network (CNN) building framework for designing real-time CNNs. We validate our models by creat- ing a real-time vision system which accomplishes the tasks of face detection, gender classification and emotion classification simultaneously in one blended step using our proposed CNN architecture. After presenting the details of the training pro- cedure setup we proceed to evaluate on standard benchmark sets. We report accuraciesdoi:10.22214/ijraset.2021.36459 fatcat:okxnlne4drewdevwnpsulnodya