| 摘要: |
| 目的 分析基于AI设计的文本视觉问答模型的有效性，旨在利用AI设计更好地指导当前AI模型的构建，提升模型效果和用户体验。方法 以传统文本视觉问答框架为基础，结合AI设计改进当前模型。具体包括加强基于场景设计原则的关系挖掘，根据不同理解层次需求的答案 |
| 关键词: AI设计 AI 文本视觉问答 认知差异 |
| DOI：10.19554/j.cnki.1001-3563.2021.06.002 |
| 分类号:TB472 |
| 基金项目:长江学者奖励项目(FRF-TP-18-010C1);国家重大专项课题(2018YFB0704301);北科大顺德研究生项目(BK19AE011) |
|
| Text-based Visual Question Answering with AI Design |
|
JIN Zan-xia1, QIN Jing-yan1, YIN Xu-cheng1,2
|
|
(1.University of Science and Technology Beijing, Beijing 100083, China;2.Shunde Graduate School, University of Science and Technology Beijing, Foshan 528399, China)
|
| Abstract: |
| It analyzes the effectiveness of the text visual question answering model based on AI design, aiming to better guide the construction of current artificial intelligence models with AI design, and improve model performance and user experience. It is based on the traditional text visual question answering framework, and the current model can be improved by combining AI design. Specifically, it includes strengthening relationship mining based on the principles of scenario design, predicting answer |
| Key words: AI design AI text-based visual question answering cognitive differences |
