Publisher Correction: Predicting drug–protein interaction using quasi-visual question answering system
نویسندگان
چکیده
منابع مشابه
Visual Question Answering Using Various Methods
This project tries to apply deep learning tools to enable computer answering question by looking at images. In this project, the visual question answering dataset[1] is introduced. This dataset consists of 204,721 real images, 614,164 question and 50,000 abstract scenes, 150,000 questions. Various methods are reproduced. The analysis on different models are presented.
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Multimodal learning between images and language has gained attention of researchers over the past few years. Using recent deep learning techniques, specifically end-to-end trainable artificial neural networks, performance in tasks like automatic image captioning, bidirectional sentence and image retrieval have been significantly improved. Recently, as a further exploration of present artificial...
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The investigation presented in this paper is a novel method in question answering (QA) that enables a QA system to gain performance through reuse of information in the answer to one question to answer another related question. Our analysis shows that a pair of question in a general open domain QA can have embedding relation through their mentions of noun phrase expressions. We present methods f...
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Visual question answering (VQA) is an interesting learning setting for evaluating the abilities and shortcomings of current systems for image understanding. Many of the recently proposed VQA systems include attention or memory mechanisms designed to support “reasoning”. For multiple-choice VQA, nearly all of these systems train a multi-class classifier on image and question features to predict ...
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In recent years, visual question answering (VQA) has become topical as a long-term goal to drive computer vision and multi-disciplinary AI research. The premise of VQA’s significance, is that both the image and textual question need to be well understood and mutually grounded in order to infer the correct answer. However, current VQA models perhaps ‘understand’ less than initially hoped, and in...
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ژورنال
عنوان ژورنال: Nature Machine Intelligence
سال: 2020
ISSN: 2522-5839
DOI: 10.1038/s42256-020-0224-z