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  2. Stereo Coupled Active Contours Tat-Jen Cham Roberto Cipolla…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/cham-cipollaCVPR97.pdf
    9 Aug 2005: Table 1 showhow different tracking modes can be effected. For exam-ple if a rigid curve is to be tracked under variable epipolargeometry (eg.
  3. 9 Aug 2005: another. Possible ways to model images include, for exam-ple, creating a set of pixel values, a frequency-based representation composed of Fouriercoefficients, or a grid of binary digits representing the
  4. Article Submitted to Computer Speech and Language Automatic…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/kim_csl04.pdf
    9 Aug 2005: of capitalisation generation are exam-ined for reference word sequences and reference punctuation marks.
  5. Named Entity Recognition from Speechand Its Use in the ...

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/kim_thesis.pdf
    9 Aug 2005: Named Entity Recognition from Speechand Its Use in the Generation of. Enhanced Speech Recognition Output. Ji-Hwan Kim. Darwin College, University of Cambridge. and. Cambridge University Engineering Department. August 2001. Thesis submitted to the
  6. Parcel:feature subset selectionin variable cost domains M.J.J. Scott, …

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/Scott_tr323.pdf
    9 Aug 2005: distributions. As we increase the number of features, without increasing the number of exam-ples, we create an ever more sparsely populated space.
  7. A Probabilistic Framework for Perceptual Grouping of Features for ...

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/yow_fg96_1.pdf
    9 Aug 2005: For efficiency, the geometric feature vector & is exam-ined first. If the feature vector fails to be a valid instance of.
  8. TODO: This is a placeholder. Final title will be filled later.

    mi.eng.cam.ac.uk/reports/svr-ftp/liao_interspeech05.pdf
    26 Sep 2005: SPLICE [1] is one recent exam-ple of this approach. Alternatively in model-based approaches,the parameters of the system are altered to reflect speech in thenew acoustic environment.
  9. Face Recognition with Image Sets Using Manifold Density Divergence ...

    mi.eng.cam.ac.uk/reports/svr-ftp/oa214_CVPR_2005_paper1.pdf
    8 Aug 2005: asfaces with grossly incorrect scales – see Figure 9 for exam-ples of successfully removed false positives.
  10. Contour-Based Learning for Object Detection Jamie ShottonDepartment…

    mi.eng.cam.ac.uk/reports/svr-ftp/shotton_iccv05.pdf
    8 Aug 2005: Training examplesEach training image can generate multiple training exam-ples. Each example is a vector of feature responses takenat a particular centroid and is given a binary target value,positive, meaning ... After each round, all training exam-ples
  11. 8 Aug 2005: exam-ple,by AthitsosandSclaroff for handposeestimation[1] andShakhnarovich et al.

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