An Efficient Approach for Customer Emotion Analytics Using Deep Learning

Author:

Kausalliya R.,Usman Barakkath Nisha,Abdullah R. Yasir

Publisher

Springer Nature Singapore

Reference15 articles.

1. Naami1 A, Hezarkhani S (2018) The impact of emotion on customers’ behavioral responses. Revista Publicando 5(15)(2):679–710. ISSN 1390-9304

2. D’Agostino R, Schmidt T (2020) EMOTIONET: a multi-convolutional neural network hierarchical approach to facial and emotional classification using TPUs. In: 2020 IEEE international conference on engineering, technology and innovation (ICE/ITMC)

3. Mellouka W, Handouzia W (2020) Facial emotion recognition using deep learning: review and insights. In: the 2nd international workshop on the future of internet of everything (FIoE), 9–12 August 2020, Leuven, Belgium

4. Li J, Oussalah M (2010) Automatic face recognition emotion system. In: 2010 IEEE 9th international conference on cyberntic intelligent systems

5. Widanagamaachchi WN, Dharmaratne AT (2009) Emotion recognition with image processing and neural networks. University of Colombo School of Computing, Sri Lanka

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