【VQA文献阅读】VQA-Med: Overview of the Medical Visual Question Answering Task at ImageCLEF 2019,程序员大本营,技术文章内容聚合第一站。
This paper describes the participation of MIT, Manipal in the ImageCLEF 2019 VQA-Med task. The goal of the task was to build a system that takes as input a medical image and a clinically relevant question, and generates a clinically relevant answer to the question by using the medical ...
Tlemcen University at ImageCLEF 2019 Visual Question Answering Task. In this paper we describe our methodology of techno team participa-tion at ImageCLEF Medical Visual Question Answering 2019 task. VQA-Med task is a challenge which combines computer vision with Natural Language Pro-cessing (NLP)...
MIT Manipal at ImageCLEF 2019 Visual Question Answering in Medical Domain This paper describes the participation of MIT, Manipal in the ImageCLEF 2019 VQA-Med task. The goal of the task was to build a system that takes as input a medical image and a clinically relevant question, and generate...
Ben Abacha, A., Hasan, S.A., Datla, V.V., Liu, J., Demner-Fushman, D., Müller, H.: VQA-Med: overview of the medical visual question answering task at ImageCLEF 2019. In: CLEF2019 Working Notes. CEUR Workshop Proceedings, CEUR-WS.org, Lugano, Switzerland, 09–12 September 201...
caption information, concepts and 7 sub-classes denoting the image radiology modality. The task concentrates on extracting Unified Medical Language System (UMLS®) Concept Unique Identifiers (CUIs) and can also be used as a first step towards theMedical Visual Question Answering (VQA-Med)task. ...
Multi-modal multi-head self-attention for medical VQA simple fusion strategy that uses multi-head self-attention to combine medical images and questions of the VQA-Med dataset of the ImageCLEF 2019 challenge... V Joshi,P Mitra,S Bose - 《Multimedia Tools & Applications》 被引量: 0发表: 202...