Vector Road Map Registration to Oblique Wide Area Motion Imagery by Exploiting Vehicle Movements

2016 ◽  
Vol 2016 (3) ◽  
pp. 1-8 ◽  
Author(s):  
Ahmed Elliethy ◽  
Gaurav Sharma
Keyword(s):  
Wide Area ◽  
Road Map ◽  
Motion Imagery ◽  
Map Registration

Learning with Privileged Information for Improved Target Classification

2014 ◽  
Vol 2 (3) ◽  
pp. 50-66 ◽  
Author(s):  
Roman Ilin ◽  
Simon Streltsov ◽  
Rauf Izmailov
Keyword(s):  
Classification Accuracy ◽  
Wide Area ◽  
Future Research ◽  
Target Classification ◽  
Privileged Information ◽  
Training Time ◽  
Additional Information ◽  
Motion Imagery ◽  
Learning Using Privileged Information

This work considers “Learning Using Privileged Information” (LUPI) paradigm. LUPI improves classification accuracy by incorporating additional information available at training time and not available during testing. In this contribution, the LUPI paradigm is tested on a Wide Area Motion Imagery (WAMI) dataset and on images from the Caltech 101 dataset. In both cases a consistent improvement in classification accuracy is observed. The results are discussed and the directions of future research are outlined.

Camera models for the wright patterson air force base (WPAFB) 2009 wide-area motion imagery (WAMI) data set

2015 ◽  
Vol 30 (6) ◽  
pp. 4-15 ◽  
Author(s):  
Curtis Cohenour ◽  
Frank van Graas ◽  
Rebecca Price ◽  
Todd Rovito
Keyword(s):  
Air Force ◽  
Wide Area ◽  
Data Set ◽  
Motion Imagery ◽  
Air Force Base
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