Facial Emotion Recognition Using Deep Convolutional Neural Network
Title | Facial Emotion Recognition Using Deep Convolutional Neural Network |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Pranav, E., Kamal, S., Chandran, C. Satheesh, Supriya, M. H. |
Conference Name | 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS) |
Keywords | Adam, artificial intelligence, Brain modeling, classification, classification systems, Computational modeling, convolution, convolutional neural nets, convolutional neural networks, deep convolutional neural network, deep learning algorithms, emotion recognition, face recognition, facial emotion recognition, facial recognition, feedback analysis, Human Behavior, human facial emotions, image classification, learning (artificial intelligence), machine learning, Metrics, Pattern recognition, pubcrawl, recommendation systems, recommender systems, resilience, Resiliency |
Abstract | The rapid growth of artificial intelligence has contributed a lot to the technology world. As the traditional algorithms failed to meet the human needs in real time, Machine learning and deep learning algorithms have gained great success in different applications such as classification systems, recommendation systems, pattern recognition etc. Emotion plays a vital role in determining the thoughts, behaviour and feeling of a human. An emotion recognition system can be built by utilizing the benefits of deep learning and different applications such as feedback analysis, face unlocking etc. can be implemented with good accuracy. The main focus of this work is to create a Deep Convolutional Neural Network (DCNN) model that classifies 5 different human facial emotions. The model is trained, tested and validated using the manually collected image dataset. |
DOI | 10.1109/ICACCS48705.2020.9074302 |
Citation Key | pranav_facial_2020 |
- facial emotion recognition
- Resiliency
- resilience
- recommender systems
- recommendation systems
- pubcrawl
- Pattern recognition
- Metrics
- machine learning
- learning (artificial intelligence)
- image classification
- human facial emotions
- Human behavior
- feedback analysis
- facial recognition
- face recognition
- emotion recognition
- deep learning algorithms
- deep convolutional neural network
- convolutional neural networks
- convolutional neural nets
- convolution
- Computational modeling
- classification systems
- classification
- Brain modeling
- Artificial Intelligence
- Adam