An unsupervised augmentation framework for deep learning based geospatial object detection: A summary of results

Mathematics

• Object Detection 100%
• Augmentation 67%
• Learning 51%
• Object 38%
• Framework 32%
• Angle 23%
• Rectangle 16%
• Training 12%
• Urban Planning 10%
• Sustainable Development 9%
• Network Architecture 8%
• Remote Sensing 8%
• Topography 7%
• Surveillance 7%
• Census 7%
• Buildings 7%
• Truth 5%
• Planning 5%
• Experimental Results 5%
• Context 3%

Earth & Environmental Sciences

• learning 46%
• agricultural management 35%
• detection 33%
• urban planning 28%
• census 27%
• surveillance 27%
• state of the art 24%
• farm 24%
• sustainable development 23%
• vehicle 22%
• topography 20%
• remote sensing 18%
• planning 17%
• need 15%

Engineering & Materials Science

• Object detection 58%
• Deep learning 50%
• Urban planning 35%
• Topography 32%
• Remote sensing 29%
• Farms 27%
• Network architecture 26%
• Sustainable development 25%