Image caption generation using transfer learning

Radosław Kopiński, Karol Antczak
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Abstract

This paper describes an image caption generation system using deep neural networks. The model is trained to maximize the probability of generated sentence, given the image. The model utilizes transfer learning in the form of pretrained convolutional neural networks to preprocess the image data. The datasets are composed of a still photographs and associated with it, five captions in English language. Constructed model is compared to other similarly constructed models using BLEU score system and ways to further improve its performance are proposed.
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利用迁移学习生成图像标题
本文介绍了一种使用深度神经网络的图像标题生成系统。该模型的训练目的是在给定图像的情况下,最大限度地提高生成句子的概率。该模型利用预训练卷积神经网络形式的迁移学习来预处理图像数据。数据集由一张静态照片和五个英文标题组成。利用 BLEU 评分系统将构建的模型与其他类似模型进行了比较,并提出了进一步提高其性能的方法。
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