MuVAM: A Multi-View Attention-based Model for Medical Visual Question Answering

no code implementations • 7 Jul 2021 • Haiwei Pan, Shuning He, Kejia Zhang, Bo Qu, Chunling Chen, Kun Shi

Since most current medical VQA models focus on visual content, ignoring the importance of text, this paper proposes a multi-view attention-based model(MuVAM) for medical visual question answering which integrates the high-level semantics of medical images on the basis of text description.

Medical Visual Question Answering Missing Labels +2

Deep Attributed Network Representation Learning via Attribute Enhanced Neighborhood

no code implementations • 12 Apr 2021 • Cong Li, Min Shi, Bo Qu, Xiang Li

In this paper, we propose a deep attributed network representation learning via attribute enhanced neighborhood (DANRL-ANE) model to improve the robustness and effectiveness of node representations.

Attribute Link Prediction +2