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Facial expression recognition algorithm based on deep convolution neural network

机译:基于深度卷积神经网络的面部表情识别算法

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This paper presents algorithms for smile detection and facial expression recognition. The developed algorithms are based on the implementation of a relatively new approach in the field of deep machine learning - a convolutional neural network. The aim of this network is to classify facial images into one of the six types of emotions. The studying of algorithms was carried using face images from the CMU MultiPie database. To accelerate the neural network operation, the training and testing processes were performed parallel, on a large number of independent streams on GPU. Fo r developed models there were given metrics of quality.
机译:本文提出了微笑检测和面部表情识别算法。所开发的算法基于深度机器学习领域中一种相对较新方法的实现-卷积神经网络。该网络的目的是将面部图像分类为六种情绪中的一种。算法的研究是使用来自CMU MultiPie数据库的面部图像进行的。为了加速神经网络的运行,在GPU上的大量独立流上并行执行了训练和测试过程。对于已开发的模型,将给出质量度量。

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