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@article{165802,
        author = {Dr. Latha H N and Dr. Gayathri M S   and Dr. Kiran Bailey},
        title = {Models for Emotion Detection and Music Recommendation System using SR-GAN },
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {1},
        pages = {2049-2055},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=165802},
        abstract = {Emotions are an important part of our life. A living being cannot live without emotions. The emotion of a person is affected by many things in and around it. A person's likes and dislikes vary according to his/her current emotion. Hence if we know the mood of the person we could recommend him/her the products that he would like to have during that situation. In this paper we have proposed a system which predicts the facial emotion of the person and then recommends a song to the person. We have used the FER2013 [9] dataset for this purpose and have used different techniques for data generation, Image Super Resolution, and classification. A Fine Tuned Swin transformer model was used for classification.  There were seven classes (emotions) in the dataset. The model could achieve an accuracy of 66.8% on the test-set with a best recall of 0.92 for disgust and happy classes and lowest recall of 0.29 for fear class.},
        keywords = {Classification, Recommendation, Emotion, Generative Adversarial Network, Transformers},
        month = {June},
        }