VGG-16 and Optimized CNN for Emotion Classification

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Amornvit Vatcharaphrueksadee
Rattikarn Viboonpanich
Puttakul Sakul-ang
Maleerat Maliyaem


This paper discusses the efficiency of using VGG 16 and Optimized CNN on emotion classification of human face dataset. Facial expression can be used as a communication medium between people to express a person feeling not only what it has shown on the outside also include the inner feeling, mental situation and perspective. In this paper, 5 basic emotions have been chosen to test the highly efficient models to elaborate the model complexity of the state-of-the-art model towards its accuracy and training efficiency of the proposed models against the state-of-the-art model such as VGG16 to achieve at least 65% accuracy.

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Research Paper