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Challenges in Machine Generation of Analytic Products from Multi-Source Data Proceedings of a Workshop (2017) / Chapter Skim
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3 Session 2: Machine Learning from Image, Video, and Map Data
Pages 9-13

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 9...
... , funded by the Defense Advanced Research Projects Agency (DARPA) and the Central Intelligence Agency, which detected events from imagery based on threedimensional models created manually.
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From page 10...
... Context from semantic web increases detection/classification performance; (4) Rapid satellite revisit and event ontologies will enable classification of four-dimensional concepts and processes; and 2  The website for Terrapattern is http://www.terrapattern.com, accessed August 24, 2017.
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From page 11...
... Figure 3.2 shows the structure of LeNet, the first convolutional neural network. More recent developments in the field include graphical processing units, better understanding of non-linearities, and large annotated data sets.
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From page 12...
... This temporal search problem in surveillance is difficult, he stated, because, most of the time, nothing of interest is happening in the footage. He noted that data sets drive research in vision because one has to build a data set that addresses the problem in need of a solution.
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From page 13...
... Hoogs noted that neuroscientists are already using computer vision research to map detailed functional brain studies. Jason Duncan, MITRE, noted that while deep learning shows great successes if there is good training data, it is still important to know how to solve problems with limited data sets.
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Key Terms

  • machine learning
  • computer vision
  • satellite imagery
  • training data
  • neural networks

  • video analytics
  • convolutional neural
  • neural network
  • adversarial data
  • video research

  • vehicle video
  • recurrent neural
  • vision community
  • training set
  • chellappa explained

  • motion imagery
  • unmanned aerial
  • aerial vehicle
  • using deep
  • deep convolutional

  • using data
  • minimum training
  • video processing
  • labeled training
  • combining machine

  • video explores
  • extract deep
  • established data
  • doing machine
  • generated data


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