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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 Apr 2006: Benavente. The AR face database. TechnicalReport 24, CVC, June 1998. [14] A.

19 Sep 2006: CACM, 24(6):381395,1981. 3. [5] D. Goldman, B. Curless, A. Hertzmann, and S.

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.

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

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

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

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.

25 May 2006: Thus with no loss of accuracy Equation 9 isrewritten in the form of Equation 24.

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.

14 Sep 2006: Pattern Analysis andMachine Intelligence, 24(6):748–763, 2002. [22] S. Obdržálek and J. ... ACM Siggraph, 2004. [24] Carsten Rother, Sanjiv Kumar, Vladimir Kolmogorov,and Andrew Blake.

22 Nov 2006: In addition to training GI models for BN systems theuse of Gender Dependent (GD) models has been found tobe advantageous [24]. ... 0.16 0.18 0.2 0.22 0.24 0.2612. 14. 16. 18. 20. 22.

21 Sep 2006: Pattern Recognition Letters, 24(2003):2743–2749, 2003. 8. O. Yamaguchi, K. Fukui, and K.

22 Nov 2006: This sensitivity to outliers is a well known feature of the MMI criterion [24]. ... j))}. (24). Each Gaussian component is assumed to be independent of all others.

19 Sep 2006: 3b. A simple way of measuring the silhouette coherence using theconcept of visual hull [24] is. ... pp. 245–262, 2001. [24] A. Laurentini, “The visual hull concept for silhouettebased image understanding,”IEEE Trans.

22 Nov 2006: Km(Oi, Oj ; λ(1)) (24)where Kl(Oi, Oj ; λ) is the dot-product of the log-likelihoodratios and Kc(Oi, Oj ; λ(1)), Km(Oi, Oj ; λ(1)), etc., ... than in the ML case. This is because the MMI base-line performs much better than the ML baseline

21 Sep 2006: The average frame rate is 24.1 frames per second(fps)). That is to say, the system can run inreal-time.

21 Nov 2006: b. . . . . (24). One candidate for estimating the decision bound-ary is the Support Vector Machine (SVM).

22 May 2006: Communications of theACM, 24(6):381–395, 1981. 15. [5] A. H. Gee, R. ... H. Berman. Engineering a freehand 3Dultrasound system. Pattern Recognition Letters, 24:757–777, 2003.

17 Feb 2006: 24]). Briefly, we estimate multivariate Gaussian components using the ExpectationMaximization (EM) algorithm [14], initialized by k-means clustering. ... appearance. IJCV, 14:5–24, 1995.34. S. Palanivel, B. S. Venkatesh, and B Yegnanarayana.