Semantic Scholar Open Access 2023

Deep Learning based Content Recommendation using Facial Emotions

Anil Kumar P. M. Kumar G. Teja Gandamala Pavan G. Shashank

Abstrak

The proposed method utilizes emotional interaction capabilities to boost the user's emotions. The proposed recommender application would serve as a personal assistant for analysing the user's emotions. The process of human emotion prediction on the facial expressions of the user. With the eye sensor, the program may identify the user's emotions (such as happy, sad, fear, disgust, surprise, and anger). Furthermore, the integrated Artificial Intelligence (AI) based algorithm intends to transform the user's emotions from negative to positive by providing suitable recommendations. Since media has a strong effect on one's emotions in today's world, the proposed model recommends movies, music, and books to improve users' emotions. Depending on the user's emotions, various activities such as watching movies, listening to songs, and reading books will be recommended.

Penulis (5)

Anil Kumar

P. M. Kumar

G. Teja

Gandamala Pavan

G. Shashank

Format Sitasi

APA MLA BibTeX

Kumar, A., Kumar, P.M., Teja, G., Pavan, G., Shashank, G. (2023). Deep Learning based Content Recommendation using Facial Emotions. https://doi.org/10.1109/ICOEI56765.2023.10125608

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Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Sumber Database: Semantic Scholar
DOI: 10.1109/ICOEI56765.2023.10125608
Akses: Open Access ✓