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1 - 10 of 48 search results for TALK:Vb20 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. Royal Society Meeting on Geometry in Computer Vision

    mi.eng.cam.ac.uk/~cipolla/royal_society.html
    28 Nov 2006: Session 3: Grouping and Matching. Thursday 24 July, 09.30-12.30 (Chair: Dr A. ... Session 4: Geometry and Statistics. Thursday 24 July, 14.00-17.40 (Chair: Dr R.

  3. Machine Learning for Speech & LanguageProcessing Mark Gales 28 ...

    mi.eng.cam.ac.uk/~mjfg/FCSW_talk.pdf
    19 Jul 2006: 5. 10. 108. 64. 20. 24. 68. 10. 0. 0.05. 0.1.

  4. Face Set Classification using Maximally Probable Mutual Modes Ognjen…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ICPR06.pdf
    29 Apr 2006: average 92.0 64.1 58.3 17.0std 7.8 9.2 24.3 8.8. video sequences of the person in arbitrary motion (signif-icant translation, yaw and pitch, ... cluded and expression variant faces from a single sample per class.PAMI, 24(6), 2002.

  5. Modelling Dependencies in SequenceClassification: Augmented…

    mi.eng.cam.ac.uk/~mjfg/gales_UEA06.pdf
    22 Nov 2006: Cambridge UniversityEngineering Department. University of East Anglia Seminar 24. Modelling Dependencies in Sequence Classification: Augmented Statistical Models. ... Comp.EER (%). GMM A-GMM. 128 12.17 8.62256 11.24 7.88512 11.13 7.481024 10.43† 7.31.

  6. EUROGRAPHICS 2006 / E. Gröller and L. Szirmay-Kalos(Guest Editors) ...

    mi.eng.cam.ac.uk/reports/svr-ftp/hernandez_eg06.pdf
    19 Sep 2006: Cambridge University Press, 1999. [FB81] FISCHLER M., BOLLES R.: Random sample consensus:A paradigm for model-fitting with applications to image analysisand automated cartography.CACM 24, 6 (1981), 381–395.

  7. AUGMENTED STATISTICAL MODELS FOR SPEECH RECOGNITION M.I. Layton and…

    mi.eng.cam.ac.uk/~mjfg/layton_ICASSP06.pdf
    22 Nov 2006: HMM ML – 29.4 27.3C-Aug ML CML 24.2 –. HMM MMI – 25.3 24.8C-Aug MMI CML 23.4 –. Table 2. Classification error on the TIMIT core test ... A point of particular interest is that despite poorer statesegmentation—the sufficient statistics fix the

  8. Multi-Sensory Face Biometric Fusion (for Personal Identification)…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_OTCBVS06.pdf
    19 Mar 2006: 24] P. S. Penev. Dimensionality reduction by sparsification in a local-features representation of human faces. ... Ross and A. Jain. Information fusion in biometrics.PatternRecognition Letters, 24(13):2115–2125, 2003.

  9. Augmented Statistical Models for SpeechRecognition Mark Gales &…

    mi.eng.cam.ac.uk/~mjfg/Edin_talk.pdf
    5 Jul 2006: Cambridge UniversityEngineering Department. Trajectory Models For Speech Processing Workshop 24. Augmented Statistical Models for Speech Recognition.

  10. Automatic Cast Listing in Feature-Length Films with Anisotropic…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_CVPR06.pdf
    21 Mar 2006: Due to the smoothness of faces, each track corre-sponds to an appearance manifold [2, 22, 24], as illustratedin Fig. ... 24] B. Moghaddam and A. Pentland. Principal manifolds and probabilis-tic subspaces for visual recognition.PAMI, 24(6), 2002.2, 3.

  11. Temporally Varying Model Parameters forLarge Vocabulary Continuous…

    mi.eng.cam.ac.uk/~mjfg/sim_INTER05.pdf
    22 Nov 2006: ãtj = max{atj , amin} (24). whereãtj is the floored scale factor andamin is the scale floor.In this paper,amin of 0.1 was used.

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