Search Results - "Meinhold, Renee T."

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  1. 1

    Compact Midwave Imaging System: Results from an Airborne Demonstration by Kelly, Michael A., Carr, James L., Wu, Dong L., Goldberg, Arnold C., Papusha, Ivan, Meinhold, Renee T.

    Published in Remote sensing (Basel, Switzerland) (01-02-2022)
    “…The Compact Midwave Imaging System (CMIS) is a wide field of view, multi-angle, multi-spectral push frame imager that relies on the forward motion of the…”
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    Journal Article
  2. 2

    Compassionately Conservative Balanced Cuts for Image Segmentation by Cahill, Nathan D., Hayes, Tyler L., Meinhold, Renee T., Hamilton, John F.

    “…The Normalized Cut (NCut) objective function, widely used in data clustering and image segmentation, quantifies the cost of graph partitioning in a way that…”
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    Conference Proceeding
  3. 3

    Robust Path-based Image Segmentation Using Superpixel Denoising by Meinhold, Renee T

    Published 01-01-2018
    “…Clustering is the important task of partitioning data into groups with similar characteristics, with one category being spectral clustering where data points…”
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    Dissertation
  4. 4

    Efficiently computing piecewise flat embeddings for data clustering and image segmentation by Meinhold, Renee T., Hayes, Tyler L., Cahill, Nathan D.

    “…Image segmentation is a popular area of research in computer vision that has many applications in automated image processing. A recent technique called…”
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    Conference Proceeding
  5. 5

    Efficiently Computing Piecewise Flat Embeddings for Data Clustering and Image Segmentation by Meinhold, Renee T, Hayes, Tyler L, Cahill, Nathan D

    Published 19-12-2016
    “…Image segmentation is a popular area of research in computer vision that has many applications in automated image processing. A recent technique called…”
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    Journal Article
  6. 6

    Compassionately Conservative Balanced Cuts for Image Segmentation by Cahill, Nathan D, Hayes, Tyler L, Meinhold, Renee T, Hamilton, John F

    Published 27-03-2018
    “…The Normalized Cut (NCut) objective function, widely used in data clustering and image segmentation, quantifies the cost of graph partitioning in a way that…”
    Get full text
    Journal Article