Expert Systems with Applications: An International Journal
Facial feature model for emotion recognition using fuzzy reasoning
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
Interval type-2 fuzzy model for emotion recognition from facial expression
PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence
Image morphing: transfer learning between tasks that have multiple outputs
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
Human emotion recognition from videos using spatio-temporal and audio features
The Visual Computer: International Journal of Computer Graphics
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This research aims at developing "Humanoid Robots" that can carry out intellectual conversation with human beings. The first step in this direction is to recognize human emotions by a computer using neural network. In this paper all six universally recognized basic emotions namely angry, disgust, fear, happy, sad and surprise along with neutral one are recognized. Multilayer Perceptron (MLP) and Generalized Feed Forward Neural Network (GFFNN) are employed and their performance is compared. Discrete Cosine Transform (DCT) and Statistical Parameters are used for feature extraction. The authors achieved 100% recognition rate on training data set (Seen examples) and test data set (Unseen examples).