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Generating Chinese Poems from Images Based on Neural Network

机译:基于神经网络的图像汉诗创作

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Chinese classical poetry generation from images is an overwhelmingly challenging work in the field of artificial intelligence. Inspired by recent advances in automatically generating description of an image and Chinese poem generation, in this paper, we present a generative model based on deep recurrent framework that describes images in the form of poems. Our model consists of two parts, one is to extract information according to the semantics presented in images, and the other is to generate each line of the poem incrementally according to the extracted semantic information from the images by a recurrent neural network. Experimental results thoroughly demonstrate the effectiveness of our approach by manual evaluation.
机译:从图像产生的中国古典诗歌在人工智能领域是一项极具挑战性的工作。受自动生成图像描述和中国诗歌生成的最新进展启发,本文提出了一种基于深度递归框架的生成模型,该模型以诗歌形式描述图像。我们的模型由两部分组成,一是根据图像中呈现的语义提取信息,二是根据递归神经网络根据从图像中提取的语义信息,逐步生成诗歌的每一行。实验结果通过人工评估彻底证明了我们方法的有效性。

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