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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Larsen, Rasmus
Technical University of Denmark
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (11/11 displayed)
- 2015Dictionary Based Segmentation in Volumescitations
- 2014Surface Detection using Round Cutcitations
- 2014Pattern recognition approach to quantify the atomic structure of graphenecitations
- 2014Structure Identification in High-Resolution Transmission Electron Microscopic Imagescitations
- 2014Quantification Tools for Analyzing Tomograms of Energy Materials
- 2013Automated Structure Detection in HRTEM Images: An Example with Graphene
- 2013Quantitative Analysis of Micro-Structure in Meat Emulsions from Grating-Based Multimodal X-Ray Tomography
- 2012Large scale tracking of stem cells using sparse coding and coupled graphs
- 2010Quantitative data analysis methods for 3D microstructure characterization of Solid Oxide Cells
- 2002Building and Testing a Statistical Shape Model of the Human Ear Canal
- 2002Testing for Gender Related Size and Shape Differences of the Human Ear canal using Statistical methods
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document
Testing for Gender Related Size and Shape Differences of the Human Ear canal using Statistical methods
Abstract
This work deals with the analysis of the shape of the humanear canal. It is described how a dense surface point distributionmodel of the human ear canal is built based on a training set oflaser scanned ear impressions and a sparse set of anatomicallandmarks placed by an expert. The dense surface models are built byusing the anatomical landmarks to warp a template mesh onto allshapes in the training set.Testing the gender related differencesis done by initially reducing the dimensionality using principalcomponent analysis of the vertices of the warped meshes. The numberof components to retain is chosen using Horn's parallel analysis.Finally a multivariate analysis of variance is performed on thesecomponents.