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  1. 1

    Multifactor Analysis of Roadheader’s Body Pose Responses during the Horizontal Cutting Process by Kai Zong, Peng Zhang, Pengjiang Wang, Shichen Fu, Yiming Li, Minjun Zhang, Miao Wu

    Published 2018-01-01
    “…Variations of the body pose parameters are influenced greatly by the cutting head load, while the influence from horizontal swing angle of the cutting arm and dip angle of coal seam is slighter. …”
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    Article
  2. 2

    Robust Initialization of Active Shape Models for Lung Segmentation in CT Scans: A Feature-Based Atlas Approach by Gurman Gill, Matthew Toews, Reinhard R. Beichel

    Published 2014-01-01
    “…Our method constructs an atlas consisting of a set of representative lung features and an average lung shape. The ASM pose parameters are found by transforming the average lung shape based on an affine transform computed from matching features between the new image and representative lung features. …”
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  3. 3

    Unsupervised delineation of chicken eggs based on the universal avian egg model by Paramate Horkaew, Sajeera Kupittayanant, Pakanit Kupittayanant

    Published 2025-08-01
    “…Accordingly, only a few model and pose parameters were required, discarding the need for large, annotated training dataset or excessive priors. …”
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  4. 4

    Analysis of Factors Affecting Random Measurement Error in LiDAR Point Cloud Feature Matching Positioning by Guoliang Liu, Wang Gao, Shuguo Pan

    Published 2025-04-01
    “…Furthermore, a simple random measurement error model based on the feature accuracy factor is used to verify the effect of parameter estimation, and the results show that the random error model can effectively reduce the error of pose parameter estimation, with an improvement effect of about 50%.…”
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