A text-based visual context modulation neural model for multimodal machine translation-Reference-Cited by-同舟云学术

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A text-based visual context modulation neural model for multimodal machine translation

Published:2020-08 Issue: Volume:136 Page:212-218
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Kwon Soonmo^ORCID,Go Byung-Hyun,Lee Jong-Hyeok

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference25 articles.

1. Show and tell: a neural image caption generator;Vinyals,2015

2. Learning to reason: end-to-end module networks for visual question answering;Hu,2017

3. FiLM: Visual reasoning with a general conditioning layer;Perez,2018

4. LIUM-CVC Submissions for WMT17 multimodal translation task;Caglayan,2017

5. Imagination improves multimodal translation;Elliott,2017

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2. CLIP-enhanced multimodal machine translation: integrating visual and label features with transformer fusion;Multimedia Tools and Applications;2024-06-05

3. Capturing natural position relationships: A neural differential equation approach;Pattern Recognition Letters;2024-02

4. Logical Synonymy Construction for Translated Texts Based on Edge Technology;Applied Mathematics and Nonlinear Sciences;2024-01-01

5. Multi-level attention for referring expression comprehension;Pattern Recognition Letters;2023-08

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