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<p><span>Deep multi-task learning is one of the most challenging research topics widely explored in the field of recognition of facial expression. Most deep learning models rely on the class labels details by eliminating the local information of the sample data which deteriorates the performance of the recognition system. This paper proposes multi-feature-based deep convolutional neural networks (D-CNN) that identify the facial expression of the human face. To enhance the accuracy ofdoi:10.11591/ijeecs.v25.i3.pp1406-1419 fatcat:txzuhv36tva25kl3y6v2rdzvma