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Emotion Recognition from Facial Expressions Using Siamese Network

Publication Type : Conference Paper

Publisher : Machine Learning and Metaheuristics Algorithms, and Applications

Source : Machine Learning and Metaheuristics Algorithms, and Applications, Springer Singapore, Singapore (2021)

Url : https://link.springer.com/chapter/10.1007%2F978-981-16-0419-5_6

ISBN : 9789811604195

Campus : Bengaluru

School : School of Engineering

Department : Computer Science

Year : 2021

Abstract : The research on automatic emotional recognition has been increased drastically because of its significant influence on various applications such as treatment of the illness, educational practices, decision making, and the development of commercial applications. Using Machine Learning (ML) models, we have been trying to determine the emotion accurately and precisely from the facial expressions. But it requires a colossal number of resources in terms of data as well as computational power and can be time-consuming during its training. To solve these complications, meta-learning has been introduced to train a model on a variety of learning tasks, which assists the model to generalize the novel learning tasks using a restricted amount of data. In this paper, we have applied one of the meta-learning techniques and proposed a model called MLARE(Meta Learning Approach to Recognize Emotions) that recognizes emotions using our in-house developed dataset AED-2 (Amrita Emotion Dataset-2) which has 56 images of subjects expressing seven basic emotions viz., disgust, sad, fear, happy, neutral, anger, and surprise. It involves the implementation of the Siamese network which estimates the similarity between the inputs. We could achieve 90.6% of overall average accuracy in recognizing emotions with the state-of-the-art method of one-shot learning tasks using the convolutional neural network in the Siamese network.

Cite this Research Publication : N. Venkata Se Maddula, Nair, L. R., Addepalli, H., and Palaniswamy, S., “Emotion Recognition from Facial Expressions Using Siamese Network”, in Machine Learning and Metaheuristics Algorithms, and Applications, Singapore, 2021.

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