Automatic Arabic Image Captioning using RNN-LSTM-Based Language Model and CNN

被引:0
|
作者
Al-Muzaini, Huda A. [1 ]
Al-Yahya, Tasniem N. [1 ]
Benhidour, Hafida [1 ]
机构
[1] King Saud Univ, Coll Comp & Informat Sci, Dept Comp Sci, Riyadh, Saudi Arabia
关键词
AI; image caption; natural language processing; neural network; deep learning convolutional neural network; recurrent neural network; long short-term memory;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The automatic generation of correct syntaxial and semantical image captions is an essential problem in Artificial Intelligence. The existence of large image caption copra such as Flickr and MS COCO have contributed to the advance of image captioning in English. However, it is still behind for Arabic given the scarcity of image caption corpus for the Arabic language. In this work, an Arabic version that is a part of the Flickr and MS COCO caption dataset is built. Moreover, a generative merge model for Arabic image captioning based on a deep RNN-LSTM and CNN model is developed. The results of the experiments are promising and suggest that the merge model can achieve excellent results for Arabic image captioning if a larger corpus is used.
引用
收藏
页码:67 / 73
页数:7
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