Facial Emotion Recognition Using Deep Convolutional Neural Network

E. Pranav, S. Kamal, C. Satheesh Chandran, M. Supriya
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引用次数: 66

Abstract

The rapid growth of artificial intelligence has contributed a lot to the technology world. As the traditional algorithms failed to meet the human needs in real time, Machine learning and deep learning algorithms have gained great success in different applications such as classification systems, recommendation systems, pattern recognition etc. Emotion plays a vital role in determining the thoughts, behaviour and feeling of a human. An emotion recognition system can be built by utilizing the benefits of deep learning and different applications such as feedback analysis, face unlocking etc. can be implemented with good accuracy. The main focus of this work is to create a Deep Convolutional Neural Network (DCNN) model that classifies 5 different human facial emotions. The model is trained, tested and validated using the manually collected image dataset.
基于深度卷积神经网络的面部情绪识别
人工智能的快速发展为科技界做出了巨大贡献。由于传统的算法无法满足人类的实时需求,机器学习和深度学习算法在分类系统、推荐系统、模式识别等不同的应用中取得了巨大的成功。情感在决定一个人的思想、行为和感觉方面起着至关重要的作用。利用深度学习的优势,可以构建一个情感识别系统,并且可以很准确地实现反馈分析、人脸解锁等不同的应用。这项工作的主要重点是创建一个深度卷积神经网络(DCNN)模型,对5种不同的人类面部情绪进行分类。使用人工采集的图像数据集对模型进行训练、测试和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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