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The Image Analytics Project enables scientific discovery by:  

  • Understanding scientific imagery, including
    • traditional imagery forms and sizes
    • advanced imagery forms and sizes (including very large images)
  • Characterizing and evaluating sensors and processors of scientific imagery, including
    • traditional sensors and architectures
    • advanced, distributed, interactive sensors and architectures
  • Organizing scientific domain knowledge
    • minimizing error and maximizing access through image processing, machine learning, and distributed technologies
  • Understanding and interpreting scientific domain knowledge
    • enabling a breadth and depth of insight not possible by manual means through the use of image processing technologies to search, classify, visualize, and interpret massive amounts of scientific imagery
  • Using scientific knowledge in new and unexpected ways 
    •  enabling the ability to collaborate, investigate, and innovate in ways not possible before
  • Measuring the quality and applicability of domain-specific
    • image data processing tools
    • image data processing infrastructures
    • image data representations



Created May 10, 2018, Updated July 7, 2021