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1 Jul 2002: concept-state can itself be afinite state network[24]. ... 269–271. [24] S Miller, R Bobrow, R Schwartz, and R Ingria, “Statisticallanguage processing using hidden understanding models,” inProc Human Language Technology Workshop, Plainsboro,NJ, 1994

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12 May 2003: Belongie,J. Malik, and J. Puzicha. Shapematchingandobjectrecognitionusingshapecontexts. IEEE Trans.PatternAnalysisand Machine Intell., 24(4):509–522,April 2002.

27 Jul 2020: Experiments on the Resource Management (RM) corpus and a subset of the Switchboard corpus show that, relative to standard HMM baseline, a reduction word error rate (WER) of 24.3% relative

27 Jul 2020: The broadcast news audio was transcribed using a 2-pass gender-dependent HTK speech recogniser which ran at 50 times real time and gave an overall word error rate of

6 Nov 2000: Some discriminative training schemes, such as frame-discrimination [14, 24], try to over-generate training set con-fusions to improve generalisation. ... In [24] it was shownthat the improvements obtained by FD were at least as goodas those reported by

27 Jul 2020: Both techniques yield a significant reduction in perplexity over the baseline trigram language model when faced with multi-domain test text, the mixture-based model giving a 24% reduction and the

14 Sep 2006: 24, 18]. Both systems group an image’sspatial features, performing a global annealing optimizationthat propagates the certainty at distinct person-boundaries touncertain areas where those people’s outlines are ambigu-ous. ... 24] P. Tu and J.

28 Jul 2004: 4] M. Fischler and R. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysisand automated cartography.Graphics and Image Processing, 24(6):381–395, 1981.

29 Jan 2004: The LDS belongs to the subset of state space models called linear Gaussian models [24]. ... Alternatively, the derivation may bedone completely using properties of conditional Gaussian distributions and matrix algebra [24].

1 Sep 2006: 10] A. M. Martinez. Recognizing imprecisely localized, partially oc-cluded and expression variant faces from a single sample per class.PAMI, 24(6), 2002.

9 Aug 2005: One wayto make a fair comparison is to compare the “merged” SLPMsystem with a system that has 24 Gaussians per state. ... However,data sparseness causes the 24 Gaussians-per-state system to beover trained and its WER on the test set is 39.7% which is

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

8 Aug 2005: CS 4.38FL 14.8102RL 185.6105DL 0.08103. CS 4.14FL 8.7102RL 137.0105DL 0.06103. CS 3.49FL 24.94102RL 4.73105DL 5.27103. ... CS 3.07FL 27.88102RL 24.7105DL 1.126103. Figure 4: Hand template matching Rows show some of the images where using the data

10 Oct 2007: ML MPE ML MPE. S0 15.1 13.6 29.3 25.40.00 13.8 12.0 27.7 24.80.80 13.5 11.7 26.9 ... Conf. bnmdev06 bcmdev05Thresh. ML MPE ML MPE. 0.00 13.8 12.0 27.7 24.80.76 13.6 11.8 27.5 24.30.80 13.5 11.7

9 Aug 2005: #"$%&'(),""%-'"/.#-01('/-"2(3 4/0"5('65"879('%%(;:1'5<>=?@;ACBED #FD.

14 Sep 2006: IEEE Trans. Pattern Analysis and Machine Intell., 24(4):509–522,April 2002. 5. M. ... Journal of Computer Vision, 48(1):9–19, June 2002. 24. J. Vermaak, A.

1 Jun 2000: 36. 23. 35. 24. 34. 25. 33. 26. 32. 27. 31. ... 19. 3. 20. 2. 21. 1. 2223. 36. 24. 35. 25.

21 Dec 2005: related method of Riklin-Raviv and Shashua [24]. On the other hand, the 3D mor-. ... mateµ̂(Di) is given by the following expression:. µ̂(Di) =. j. αjG(Di; µj, σj), (24).

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