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Creators/Authors contains: "Liu, M."

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  1. ; ; ; ; ; ( , SIGCOMM)
    Free, publicly-accessible full text available September 1, 2024
  2. ; ; ; ; ; ( , Proceedings of the ACM SIGCOMM Internet Measurement Conference)
    Free, publicly-accessible full text available September 1, 2024
  3. ; ; ; ( , 17th USENIX Symposium on Operating Systems Design and Implementation)
    Free, publicly-accessible full text available July 1, 2024
  4. ; ; ; ( , 17th USENIX Symposium on Operating Systems Design and Implementation)
    Free, publicly-accessible full text available July 1, 2024
  5. ; ; ; ; ; ; ( , Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition)
    Free, publicly-accessible full text available January 1, 2024
  6. ; ; ; ; ; ( , European Conference on Computer Vision)
    Free, publicly-accessible full text available October 1, 2023
  7. ; ; ; ; ; ( , MRS Communications)
    Abstract

    Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature identification, and discovery of novel processing-structure–property relationships. We conclude by discussing opportunities and challenges for continued advancement of QMA, including instrumentation development, uncertainty quantification, and automatic parsing of literature data.

    Graphical abstract

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  8. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review C)
    Free, publicly-accessible full text available September 1, 2024
  9. ; ; ; ( , ACM Transactions On Graphics (TOG), Siggraph)
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  10. ; ; ; ; ( , Physical Review B)
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