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21 - 30 of 48 search results for :pc53 24 / |u:mi.eng.cam.ac.uk where 0 match all words and 48 match some words.

  1. Results that match 1 of 2 words

  2. Sparse and Semi-supervised Visual Mapping with the S3GP Oliver ...

    mi.eng.cam.ac.uk/reports/svr-ftp/williams_cvpr06.pdf
    3 Apr 2006: model. In the case of gaze tracking,the standard calibration process givesn = 80 (nl = 16);with m = 24, the S3GP takes 8s to train (24s including cal-ibration) and requires

  3. The Layout Consistent Random Field for Recognizing and Segmenting ...

    mi.eng.cam.ac.uk/reports/svr-ftp/shotton_cvpr06.pdf
    3 Apr 2006: Benavente. The AR face database. TechnicalReport 24, CVC, June 1998. [14] A.

  4. Reconstruction in the round using photometric normals. George…

    mi.eng.cam.ac.uk/reports/svr-ftp/hernandez_cvpr06.pdf
    19 Sep 2006: CACM, 24(6):381395,1981. 3. [5] D. Goldman, B. Curless, A. Hertzmann, and S.

  5. MODEL-BASED TECHNIQUES FORNOISE ROBUST SPEECH RECOGNITION Mark John…

    mi.eng.cam.ac.uk/~mjfg/thesis.pdf
    5 Jun 2006: 233.2.4 State-Based Speech Enhancement. 24. 3.3 Model-Based Techniques. 243.3.1 Linear Regression Adaptation. ... Ljm(τ ) = p(qjm(τ )|YT , M) (2.24)=. 1L(YT |M) Uj (τ )cjmbjm(y(τ ))βj (τ ). where. Uj (τ ) =. . a1j , if τ = 1N1i=2.

  6. A New Look at Filtering Techniques for Illumination Invariance ...

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_AFG06.pdf
    30 Jan 2006: FaceDB100 64.1/9.2 73.6/22.5 58.3/24.3 17.0/ 8.8FaceDB60 81.8/9.6 79.3/18.6 46.6/28.3

  7. 1 Model-Based Hand Tracking Using a HierarchicalBayesian Filter…

    mi.eng.cam.ac.uk/reports/svr-ftp/thayananthan_pami06.pdf
    14 Sep 2006: 24] andfor exemplar templates by Toyama and Blake [43].However, it is acknowledged that “one problem withexemplar sets is that they can grow exponentiallywith object complexity. ... Wetake inspiration from Jojic et al. [24] who modelleda video sequence

  8. Discriminative Adaptation for Speaker Verification C. Longworth and…

    mi.eng.cam.ac.uk/~mjfg/longworth_INTER06.pdf
    22 Nov 2006: ComponentsGMM A-GMM. EER(%) minDCF EER(%) minDCF. 128 12.17 0.5014 8.62 0.3714256 11.24 0.4704 7.88 0.3467512 11.13 0.4638 7.48

  9. IEEE TRANS. ON SAP, VOL. ?, NO. ??, ????? ...

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/mjfg_ASL.pdf
    23 Feb 2006: Gales et al.: THE CUED BROADCAST NEWS TRANSCRIPTION SYSTEM 7. developing the Cambridge 10RT broadcast news system in1998 [24]11. ... 0.16 0.18 0.2 0.22 0.24 0.2612. 14. 16. 18. 20. 22.

  10. PHASE-BASED ULTRASONICDEFORMATION ESTIMATION J. E. Lindop, G. M.…

    mi.eng.cam.ac.uk/reports/svr-ftp/lindop_tr555.pdf
    25 May 2006: Thus with no loss of accuracy Equation 9 isrewritten in the form of Equation 24.

  11. thesis.dvi

    mi.eng.cam.ac.uk/reports/svr-ftp/nock_thesis.pdf
    14 Jun 2006: 145]; an empirical comparisonof techniques is provided by [24]. The N-gram model captures only local constraints and ignores higher-level structure.Many more sophisticated models have been investigated.

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