A VQA system takes as input an image and a natural language question about the image and produces an answer consistent with the visual content of a given image.

Visual Question Answering in the Medical Domain. The year 2018 witnessed the inauguration of a special challenge for VQA in the medical domain.

VQA-Med 2019 focused on radiology images and four main categories of questions: Modality, Plane, Organ system and Abnormality.

Visual Question Answering in the Medical Domain (VQA-Med). 4 stars 1 fork Branches Tags Activity.

This is the official implementation of M2I2 for the visual question answering task in medical domain at ISBI-2023. Our proposal achieves superior accuracy.

VQA is a multidisciplinary problem which combines two modalities: text and image. It requires computer vision and NLP techniques (probably, reasoning techniques ...

Training procedure · Go into the project directory using cd VQA_Med · Run the following command to install all the dependencies you need to run this project :.

20 сент. 2023 г. · Medical visual question answering (Med-VQA) is a machine learning task that aims to create a system that can answer natural language ...

It is a dataset of clinically generated visual questions and answers about radiology images. The dataset consists of two types of questions: CLOSED and OPEN.

Our proposal achieves significantly increased accuracy in predicting answers to both closed-ended and open-ended questions, especially for open-ended questions. Не найдено: domain | Нужно включить: domain