News

Sep 24, 2018

Accorded Phase II SBIR project to address Low Shot Detection in Remote Sensing Imagery


 

With the ever-growing number of imaging satellites in orbit the job of an analyst will change from eyes on pixels to analysis of information from imagery using automated image processing like object detection and change detection. Object detection algorithms have advanced to near human performance given that there is sufficient labeled data on which to train; however, obtaining this data is costly and time consuming. On the other hand the mission is immediate and potentially urgent. A preferable solution is to build upon historical training data but enable object detectors to identify new high value objects of interest from small sets of new data labels, i.e. new low shot classes. Etegent and our partner, The University of Berkeley, International Computer Science Institute, will extend our demonstrated dual network low shot solution and investigate cutting edge approaches that leverage context to provide a comprehensive solution to the low shot problem.


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