Question answer icon. Q&A sign symbol. Speech bubbles with question and answer. ID: 357948731 收藏 加入清单 下载版权Fine Art 格式矢量图 编辑图片 以图搜图 矢量:可随意调整尺寸 大图:4067× 4067 像素·34.43 cm × 34.43 cm·300dpi·JPG 了解更多 图片套餐 常见问题: 商业用途| 授权| 授权书| 发票...
To mitigate this limitation, this paper investigates the utility of image captioning-a technique that generates one or more descriptive sentences pertaining to the content of an image-as a means to augment answer quality within the framework of VQA, leveraging a language-centric approach. Towards ...
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Previous turn top answer result QnA ID. Previous User Query previousUserQuery string Previous user query. key key string Metadata Key from Metadata dictionary used in the QnA. value value string Metadata Value from Metadata dictionary used in the QnA. Join Metadata with logicalOperation ...
We are still updating this question and answer page. If you have questions that have not covered by the links below, please feel free to contact me directly at dian@quotescover.com.About the Quote Image EditorAn Introduction of quote image graphic components Quick design What is the fastest...
A Text type question can accept a short (one-line) answer or a long (multiple-line) answer. Short-answer question By default, a text question accepts a short answer. Long-answer question You can accept multiple lines of text for your question by turning on theLong answertoggle. ...
Visual Question Answering requires com- prehending and reasoning with visual (image) and textual (question) information [47]. The mainstream of model ar- chitectures is to first learn the joint image-question repre- sentation and then predict the answer through multi-way classification. In the ...
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Answerscan be text up to 75 characters oran image. You can toggle if participants can selectone or more than one answer. You canupload an imageor choose one from ourimage library, or embed aYouTube or Vimeo video. You cannot create, edit and save games with this question type if you ar...
2. existing VQA systems learn about the properties of objects from question-answer pairs, sometimes independently of the image. 选择性的关注图像中的某些区域是很重要的策略。 我们从最近的 memory-augmented neural networks 以及 co-attention mechanism 得到启发,本文中,我们利用 memory-networks 来记忆 rare...