Image Captioning Model Using Part-of-Speech Guidance Module for Description With Diverse Vocabulary-Reference-Cited by-同舟云学术

Image Captioning Model Using Part-of-Speech Guidance Module for Description With Diverse Vocabulary

Published:2022 Issue: Volume:10 Page:45219-45229
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Bae Ju-Won¹^ORCID,Lee Soo-Hwan¹^ORCID,Kim Won-Yeol²,Seong Ju-Hyeon³^ORCID,Seo Dong-Hoan⁴^ORCID

Affiliation:

1. Department of Electronics & Electrical Engineering, Interdisciplinary Major of Maritime AI Convergence, Korea Maritime and Ocean University, Busan, South Korea

2. Artificial Intelligence Convergence Research Center for Regional Innovation, Korea Maritime & Ocean University, Busan, South Korea

3. Department of Liberal Education, Interdisciplinary Major of Maritime AI Convergence, Korea Maritime & Ocean University, Busan, South Korea

4. Division of Electronics and Electrical Information Engineering, Interdisciplinary Major of Maritime AI Convergence, Korea Maritime & Ocean University, Busan, South Korea

Funder

National Research Foundation of Korea (NRF) Grant

Korea Government [Ministry of Science and ICT (MSIT)]

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09762317.pdf?arnumber=9762317

Reference55 articles.

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2. Attention is all you need;vaswani;Proc Adv Neural Inf Process Syst,2017

3. BERT: Pre-training of deep bidirectional transformers for language understanding;devlin;arXiv 1810 04805,2018

4. Recurrent neural network based language model

5. Sequence to sequence learning with neural networks;sutskever;Proc Adv Neural Inf Process Syst,2014

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