• Uday Shankar Dikshit
• Prof. Divya Jain

Facial Emotion Recognition is in pattern these days in view of its wide application zone. With the advancement in the field of profound learning, Facial feeling acknowledgment has become a significant subject in the business. There is critical examination on it since 1960; still, it is a difficult errand for the analysts in the business. Feeling acknowledgment is utilized to perceive the feelings of an individual. Different strategies have been created to recognize the feeling of an individual from still pictures and live recordings. At the same time, the basic principle of MLP Grasp the full connection layer and classification layer, and use Python's theano library to achieve. The construction and training of CNN model based on face recognition are studied. To simplify the CNN model, the convolution and sampling layers are combined into a single layer. Based on the already trained network, greatly improve the image recognition rate.

Facial Expressions, CNN, Trained Network

"Optimization Accuracy of Facial Emotion Recognition using Convolution Deep Neural Network ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 1, page no.d253-d258, January-2022, Available :http://www.jetir.org/papers/JETIR2201334.pdf

"Optimization Accuracy of Facial Emotion Recognition using Convolution Deep Neural Network ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 1, page no. ppd253-d258, January-2022, Available at : http://www.jetir.org/papers/JETIR2201334.pdf