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Found 4 papers, 1 papers with code
TinyVQA: Compact Multimodal Deep Neural Network for Visual Question Answering on Resource-Constrained Devices
Traditional machine learning models often require powerful hardware, making them unsuitable for deployment on resource-limited devices.
Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region
With the advancement of deep learning techniques, we can now extract high-level information from the ice sheet data (e. g., estimating the ice layer thickness, predicting the ice accumulation for upcoming years, etc.).
VQA-Aid: Visual Question Answering for Post-Disaster Damage Assessment and Analysis
Visual Question Answering system integrated with Unmanned Aerial Vehicle (UAV) has a lot of potentials to advance the post-disaster damage assessment purpose.
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
This dataset demonstrates the post flooded damages of the affected areas.
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