(untitled) (International Journal of Communication Systems and Network Technologies, 2019)
Human Facial Expression Recognition (FER) is always been a challenging task for researchers. Face expressions play an important role in non-verbal communication. Nowadays, deep learning is achieving great attention in this area. But it is a tedious task to build a simple and effective architecture in deep learning. The need is to develop an architecture which is fast to train and achieves good accuracy. Therefore, for detecting human facial expressions deep learning model using a convolutional neural network(CNN) is used in image classification as these models are effective and achieve high accuracy and effictiveness for the facial expression recognition problems. This work is proposed to acquire results improvement on FER-201, JAFFE, and CK+ dataset. Python platform is used for implementation and execution of the proposed work.