Results 11 to 20 of about 51,006 (167)

Attention-Based Multimodal Deep Learning on Vision-Language Data: Models, Datasets, Tasks, Evaluation Metrics and Applications

IEEE Access, 2023
Multimodal learning has gained immense popularity due to the explosive growth in the volume of image and textual data in various domains. Vision-language heterogeneous multimodal data has been utilized to solve a variety of tasks including classification,
Priyankar Bose, Pratip Rana, Preetam Ghosh   +2 more
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Text-Image Gated Fusion Mechanism for Multimodal Aspect-based Sentiment Analysis [PDF]

Jisuanji kexue
Multimodal aspect-based sentiment analysis is an emerging task in multimodal sentiment analysis field,which aims to identify the sentiment of each given aspect in text and image.Although recent research on multimodal sentiment analysis has made ...
ZHANG Tianzhi, ZHOU Gang, LIU Hongbo, LIU Shuo, CHEN Jing
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Teaching Multimodal Literacy Through Reading and Writing Graphic Novels

Language and Literacy: A Canadian Educational e-journal, 2017
Scholarship suggests that writing teachers and instructors looking to integrate multimodal composition into their secondary or post-secondary classrooms should consider graphic novels as a mentor text for multimodal literacy.
Mike P. Cook, Jeffrey S.J. Kirchoff
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Text-image semantic relevance identification for aspect-based multimodal sentiment analysis [PDF]

PeerJ Computer Science
Aspect-based multimodal sentiment analysis (ABMSA) is an emerging task in the research of multimodal sentiment analysis, which aims to identify the sentiment of each aspect mentioned in multimodal sample.
Tianzhi Zhang, Gang Zhou, Jicang Lu, Zhibo Li, Hao Wu, Shuo Liu   +5 more
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Multimodal Fusion with Dual-Attention Based on Textual Double-Embedding Networks for Rumor Detection

Applied Sciences, 2023
Rumors may bring a negative impact on social life, and compared with pure textual rumors, online rumors with multiple modalities at the same time are more likely to mislead users and spread, so multimodal rumor detection cannot be ignored.
Huawei Han, Zunwang Ke, Xiangyang Nie, Li Dai, Wushour Slamu   +4 more
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HMTL: Heterogeneous Modality Transfer Learning for Audio-Visual Sentiment Analysis

IEEE Access, 2020
Multimodal sentiment analysis is an extended approach to traditional language-based sentiment analysis, which uses other relevant modality data. Multimodal sentiment analysis usually applies visual, textual, and acoustic representations for sentiment ...
Sanghyun Seo, Sanghyuck Na, Juntae Kim
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Covid-19 Pandemic in Political Cartoons of the American Press: An Experience of Multimodal Analysis

Научный диалог, 2021
An attempt is made to analyze the place of political cartoons in the current socio-political media discourse in the United States. The material was the cartoons published in the spring of 2020 from USA Today and Philadelphia Inquirer, the informational ...
E. M. Pozdnyakova, O. A. Blinova
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Actualization of interjections’ potential in the English-language multimodal text (based on ‘Disney Magic Kingdom Comics’)

Вестник Самарского университета: История, педагогика, филология, 2021
In the article the author analyzes interjections as signals of emotions in order to determine their functions in creating the perlocutionary effect of comics, which is especially relevant in the era of ever-increasing emotionalization of the global ...
N. V. Panina
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A film adaptation of Stephen King’s novella “Rita Hayworth and Shawshank Redemption” (1982) as an example of a multimodal translation pattern

Językoznawstwo, 2020
Recently, I came across the statement that „adaptation is a procedure for the translation of the film” (Post). Adaptation reaches not only the increasing circles of the cinema or art, but also our lives, and the very concept of adaptation undergoes ...
Wiktor Szochner
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Multimodal machine learning enables AI chatbot to diagnose ophthalmic diseases and provide high-quality medical responses

npj Digital Medicine
Chatbot-based multimodal AI holds promise for collecting medical histories and diagnosing ophthalmic diseases using textual and imaging data. This study developed and evaluated the ChatGPT-powered Intelligent Ophthalmic Multimodal Interactive Diagnostic ...
Ruiqi Ma, Qian Cheng, Jing Yao, Zhiyu Peng, Mingxu Yan, Jie Lu, Jingjing Liao, Lejin Tian, Wenjun Shu, Yunqiu Zhang, Jinghan Wang, Pengfei Jiang, Weiyi Xia, Xiaofeng Li, Lu Gan, Yue Zhao, Jiang Zhu, Bing Qin, Qin Jiang, Xiawei Wang, Xintong Lin, Haifeng Chen, Weifang Zhu, Dehui Xiang, Baoqing Nie, Jingtao Wang, Jie Guo, Kang Xue, Hongguang Cui, Jinwei Cheng, Xiangjia Zhu, Jiaxu Hong, Fei Shi, Rui Zhang, Xinjian Chen, Chen Zhao   +35 more
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