【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。
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....
If you find that our meta-learning work for MedVQA is useful, you could cite the following paper: @inproceedings{aioz_mmq_miccai21, author={Tuong Do and Binh X. Nguyen and Erman Tjiputra and Minh Tran and Quang D. Tran and Anh Nguyen}, title={Multiple Meta-model Quantifying for Medic...