Search Results - "Macrini, D."

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  1. 1

    Indexing hierarchical structures using graph spectra by Shokoufandeh, A., Macrini, D., Dickinson, S., Siddiqi, K., Zucker, S.W.

    “…Hierarchical image structures are abundant in computer vision and have been used to encode part structure, scale spaces, and a variety of multiresolution…”
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    Journal Article
  2. 2

    Hypercaloric diet prevents sexual impairment induced by maternal food restriction by Bernardi, M.M, Macrini, D.J, Teodorov, E, Bonamin, L.V, Dalboni, L.C, Coelho, C.P, Chaves-Kirsten, G.P, Florio, J.C, Queiroz-Hazarbassanov, N, Bondan, EF, Kirsten, T.B

    Published in Physiology & behavior (01-05-2017)
    “…Abstract Prenatal undernutrition impairs copulatory behavior and increases the tendency to become obese/overweight, which also reduces sexual behavior…”
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    Journal Article
  3. 3

    View-based 3-D object recognition using shock graphs by Macrini, D., Shokoufandeh, A., Dickinson, S., Siddiqi, K., Zucker, S.

    “…The shock graph is an emerging shape representation for object recognition, in which a 2-D silhouette is decomposed into a set of qualitative parts, captured…”
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    Conference Proceeding
  4. 4

    From skeletons to bone graphs: Medial abstraction for object recognition by Macrini, D., Siddiqi, K., Dickinson, S.

    “…Medial descriptions, such as shock graphs, have gained significant momentum in the shape-based object recognition community due to their invariance to…”
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    Conference Proceeding
  5. 5

    Probabilistic shape parsing for view-based object recognition by Macrini, D., Whiten, C., Laganiere, R., Greenspan, M.

    “…We present a novel probabilistic model for parsing shapes into several distinguishable parts for accurate shape recognition. This shape parsing is based on…”
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    Conference Proceeding
  6. 6

    Canonical Skeletons for Shape Matching by van Eede, M., Macrini, D., Telea, A., Sminchisescu, C., Dickinson, S.

    “…Skeletal representations of 2-D shape, including shock graphs, have become increasingly popular for shape matching and object recognition. However, it is well…”
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    Conference Proceeding