Facial Expression and Emotion Detection
The use of machines in the public has expanded widely in the most recent decades. These days, machines are utilized as a part of a wide range of businesses. As their introduction with people increment, the communication additionally needs to wind up smoother and more characteristic. Keeping in mind the end goal to accomplish this, machines must be given an ability that let them get it the encompassing condition. Exceptionally, the intentions of a person. At the point when machines are eluded, this term includes computers and robots.
During the development of this work, deep learning techniques have been used over images displaying the following facial emotions: happiness, sadness, anger, surprise, disgust, and fear. In this work, two independent methods proposed for this very task.
· The first method uses autoencoders to construct a unique representation of each emotion.
· The second method is an 8-layer convolutional neural network (CNN).
Related Conference of Facial Expression and Emotion Detection
Facial Expression and Emotion Detection Conference Speakers
- AI & Machine Learning in HealthCare & Medical Science
- Artificial Intelligence
- Artificial Neural Networks (ANN)
- Big Data Analytics
- Big Data, Data Science and Data Mining
- Cloud Computing
- Computer Vision and Image Processing
- Deep Learning
- Deep Learning Frameworks
- Facial Expression and Emotion Detection
- Internet of Things (IoT)
- Machine Learning
- Natural Language Processing (NLP) and Speech Recognition
- Pattern Recognition
- Predictive Analytics
- Robotic Process Automation (RPA)
- Virtual Reality And Augmented Reality