Cargando…
BPI-MVQA: a bi-branch model for medical visual question answering
BACKGROUND: Visual question answering in medical domain (VQA-Med) exhibits great potential for enhancing confidence in diagnosing diseases and helping patients better understand their medical conditions. One of the challenges in VQA-Med is how to better understand and combine the semantic features o...
Autores principales: | Liu, Shengyan, Zhang, Xuejie, Zhou, Xiaobing, Yang, Jian |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9052498/ https://www.ncbi.nlm.nih.gov/pubmed/35488285 http://dx.doi.org/10.1186/s12880-022-00800-x |
Ejemplares similares
-
Vision–Language Model for Visual Question Answering in Medical Imagery
por: Bazi, Yakoub, et al.
Publicado: (2023) -
Adversarial Learning with Bidirectional Attention for Visual Question Answering
por: Li, Qifeng, et al.
Publicado: (2021) -
Parallel multi-head attention and term-weighted question embedding for medical visual question answering
por: Manmadhan, Sruthy, et al.
Publicado: (2023) -
Linguistic issues behind visual question answering
por: Bernardi, Raffaella, et al.
Publicado: (2021) -
A Stacked BiLSTM Neural Network Based on Coattention Mechanism for Question Answering
por: Cai, Linqin, et al.
Publicado: (2019)