• PULAGAM SRAVANTHI

In general emotion is considered as one of the important aspects in various fields such as biomedical engineering, psychology, and mental health. Hence this is mainly used for diagnosis of human brain and psychological disorders. Till now lot of research work is conducted in order to identify the emotions from real time facial expressions but no work is completely achieved in finding all the 7 emotions from human face. Hence this motivated me to develop this current application in which we try to use several deep learning models on emotion detection from either still images or from video sequence and then check the ability of each and every individual model. The proposed system can effectively and efficiently recognizes emotions from the facial expressions of the individual user. Here we try to use several pretrained models and customized model for finding the accuracy and compare the performance of each and every model individually based on this validation loss and accuracy. By conducting various experiments on our proposed models by taking a sample facial images dataset collected from KAGGLE website and try to train the system to detect the emotions accurately.

Pre-Trained Model, Emotion Recognition, KAGGLE, psychological Disorders, and Facial Expressions.

" DEMONSTRATE THE PERFORANCE OF SEVERAL DEEPLEARNING MODELS FOR REAL TIME FACIAL EXPRESSION AND EMOTION RECOGNITION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.301-307, April-2021, Available :http://www.jetir.org/papers/JETIR2104041.pdf

" DEMONSTRATE THE PERFORANCE OF SEVERAL DEEPLEARNING MODELS FOR REAL TIME FACIAL EXPRESSION AND EMOTION RECOGNITION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp301-307, April-2021, Available at : http://www.jetir.org/papers/JETIR2104041.pdf