aspg-3-556-1791417124 20261007235204 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2020 2 1 Harsh Jain Information Technology Bharati Vidyapeeth's College of Engg, New Delhi, India Parv Bharti Information Technology Bharati Vidyapeeth's College of Engg, New Delhi, India Arun Kumar Dubey Information Technology Bharati Vidyapeeth's College of Engg, New Delhi, india; Preetika Soni Information Technology Bharati Vidyapeeth's College of Engg, New Delhi, India Detecting and analyzing emotions from human facial movements is a problem defined and developed over many years for the benefits it brings. During playback, when developing data sets, data sets with methods become more and more complex, and accuracy and difficulty increase gradually. In the given paper, we will use a deep structured learned network using the two mechanisms - Vgg and Resnet50 with deep layers to classify emotions based on input images in complex environments. Besides that, we also use learning methods combining many modern models to increase accuracy. Experimental results show that the two proposed methods have better results than some modern methods in emotional recognition problems for complex input images and some results reported in scientific studies. Particularly combined learning method gives good accuracy - 66.15% on the dataset FER2013 2020 22 30 556 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.020101 https://www.americaspg.com/journal/3/article/556 https://www.americaspg.com/storage/5492.pdf