A new in-context visual question answering dataset encompassing interleaved image and EHR data derived from MIMIC-IV and MIMIC-CXR-JPG databases.
同时,为了便于评测,让GPT-4为每个条目配置错误答案,将其构造成选择题的形式,通过这种方式,在确保语义不变的前提下,使不同VQA条目的问答形式更多样。该数据集旨在为医学多模态大模型的发展提供评测基准。详情请参见五号雷达:5radar.com/dataset?发布于 2024-06-03 12:38・IP 属地上海...
The VQA-Med dataset was also used the ImageCLEF Caption & Concept Prediction Task:https://www.imageclef.org/2021/medical/caption VQG Data: The VQG 2021 validation set contains 200 questions associated with 85 radiology images. The VQG 2021 test set includes 100 radiology images. Participants ...
Evaluated on the VQA-Med 2019 dataset, the proposed model achieved an overall classification accuracy of 0.639. The experimental results demonstrated that the proposed method has superior performance compared to existing methods on the VQA-Med 2019 dataset....
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Additionally, to verify the model's capability in visual comprehension, a novel multiple-choice medical visual understanding dataset is introduced, confirming the positive impact of focusing on visual regions of interest in advancing biomedical VQA understanding. 展开 ...
同时,为了便于评测,让GPT-4为每个条目配置错误答案,将其构造成选择题的形式,通过这种方式,在确保语义不变的前提下,使不同VQA条目的问答形式更多样。该数据集旨在为医学多模态大模型的发展提供评测基准。 详情请参见五号雷达:https://www.5radar.com/dataset?id=ecaea4b5e083d627f30a0568e2053cb6...
同时,为了便于评测,让GPT-4为每个条目配置错误答案,将其构造成选择题的形式,通过这种方式,在确保语义不变的前提下,使不同VQA条目的问答形式更多样。该数据集旨在为医学多模态大模型的发展提供评测基准。 详情请参见五号雷达:https://www.5radar.com/dataset?id=ecaea4b5e083d627f30a0568e2053cb6...
目录AbstractIntroduction MethodOverviewVQAmodule Reconstruction module Loss function Experiments Ablation studies Performance onVQAv1 andVQAv2 dataset Conclusion 总结Abstract最近,许多研究指出VQA模型容易被 内容AI:建立统一的跨媒体多模态内容理解内核 QuestionAnsweringModels fortheImageCLEF2019Challenge intheMedicalDomai...
I also generated new training data from the existing VQA-Med 2020 VQG dataset, based on contextual word embeddings and image augmentation techniques. My best VQA and VQG models achieve 44.1% and 11.6% respectively in terms of BLEU score. 展开 年份: 2020 ...