Deep Learning for Emotion Recognition

Author:

Kavitha T.1,S. Malini2,G. Senbagavalli2

Affiliation:

1. New Horizon College of Engineering (Autonomous), Visvesvaraya Technological University, India

2. AMC Engineering College, India

Abstract

Deep learning is a type of machine learning that trains a computer to recognizing speech, identifying images or making predictions. Computer vision allows machines to visualize and sense the visual world from digital images or videos. Computer vision can be used for face detection, recognition, and emotion detection. There is a growing demand for emotion analysis in the computer vision market. Expressions play an important role in the recognition of emotions for medical sentiment analysis that can be detected by a deep learning model with the help of trained classes. This chapter focuses on emotion recognition and discusses the different algorithms/architecture developed for emotion recognition using deep learning with the data set. Current research and applications based on emotion recognition are also discussed. This chapter can guide beginners in the field of emotion recognition and provide a general understanding of the latest state of art models, as well as guide the researchers looking for directions for future work.

Publisher

IGI Global

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Elevating Disease Prediction: A Stacking Ensemble Learning Approach;2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE);2024-04-26

2. Emotion Recognition Techniques with IoT and Deep Learning Technologies;Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23);2023

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