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A Facial Expression Recognition Approach Using DCNN for Autistic Children to Identify Emotions

机译:使用DCNN的自闭症儿童面部表情识别方法来识别情绪

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In this paper, an initial work of a research is discussed which is to teach young autistic children recognizing human facial expression with the help of computer vision and image processing. This paper mostly discusses the initial work of facial expression recognition using a deep convolutional neural network. The Kaggle's FER2013 dataset has been used to train and experiment with a deep convolutional neural network model. Once a satisfactory result is achieved, the dataset is modified with pictures of four different lighting conditions and each of these datasets is again trained with the same model. This is necessary for the end goal of the research which is to recognize facial expression in any possible environment. Finally, the comparison between results with different datasets is discussed and future work of the project is outlined.
机译:在本文中,讨论了一项研究的初步工作,该工作是教自闭症的幼儿借助计算机视觉和图像处理来识别人的面部表情。本文主要讨论使用深度卷积神经网络进行面部表情识别的初步工作。 Kaggle的FER2013数据集已用于训练和实验深度卷积神经网络模型。一旦获得令人满意的结果,就使用四个不同光照条件的图片修改数据集,并再次使用相同的模型训练这些数据集。这对于研究的最终目标是必要的,该最终目标是在任何可能的环境中识别面部表情。最后,讨论了不同数据集的结果之间的比较,并概述了该项目的未来工作。

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