Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis
Nanyang Technological University · University of Stirling
Abstract
Technology has enabled anyone with an Internet connection to easily create and share their ideas, opinions and content with millions of other people around the world. Much of the content being posted and consumed online is multimodal. With billions of phones, tablets and PCs shipping today with built-in cameras and a host of new video-equipped wearables like Google Glass on the horizon, the amount of video on the Internet will only continue to increase. It has become increasingly difficult for researchers to keep up with this deluge of multimodal content, let alone organize or make sense of it. Mining useful knowledge from video is a critical need that will grow exponentially, in pace with the global growth of…
Citation impact
- FWCI
- 90.11
- Percentile
- 100%
- References
- 45
Authors
4Topics & keywords
- Computer science
- Sentiment analysis
- Convolutional neural network
- Pace
- The Internet
- Deep learning
- Artificial intelligence
- Classifier (UML)