TY  - JOUR
T1  - Image Caption Generation using Object Attention Mechanism
AU  - Park, Da-Sol 
AU  - Cha, Jeong-Won 
JO  - Journal of KIISE, JOK
PY  - 2019
DA  - 2019/1/14
DO  - 10.5626/JOK.2019.46.4.369
KW  - attention mechanism
KW  - deep learning
KW  - image captioning
KW  - natural language processing
KW  - machine learning
AB  - Explosive increases in image data have led studies investigating the role of image caption generation in image expression of natural language. The current technologies for generating Korean image captions contain errors associated with object concurrence attributed to dataset translation from English datasets. In this paper, we propose a model of image caption generation employing attention as a new loss function using the extracted nouns of image references. The proposed method displayed BLEU1 0.686, BLEU2 0.557, BLEU3 0.456, BLEU4 0.372, which proves that the proposed model facilitates the resolution of high-frequency word-pair errors. We also showed that it enhances the performance compared with previous studies and reduces redundancies in the sentences. As a result, the proposed method can be used to generate a caption corpus effectively.