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Machine Learning for Speech & LanguageProcessing Mark Gales 28 ...
mi.eng.cam.ac.uk/~mjfg/FCSW_talk.pdf19 Jul 2006: Gaussianise the data for each speaker:. 20 15 10 5 0 5 10 15 200. ... 0.01. 0.02. 0.03. 0.04. 0.05. 0.06. 0.07. 0.08. 0.09. 0.1. 20 15 10 5 0 5 10 15 200. -
C:/SFWDoc/Academic/Publications/2005/BMVC_2005/FinalPaper/bmvc_05_sfwo…
mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_bmvc05.pdf21 Sep 2006: Furthermore, since the size of the ROIs may vary from one videoto the other, the final MGO images are resized to the corresponding refined images withstandard size (which is 200 200 ... 3.2 Dimension Reduction by PCA. In order to reduce the number of -
paper.dvi
mi.eng.cam.ac.uk/~mjfg/liao_INTER06.pdf22 Nov 2006: 180 190 200 210 220 2300. 50. 100. Frame. aii. Figure 3: Plot of log energy for snippet from AURORA digit string8-6-Zero-1-1-6-2, showing joint ... Asanticipated, the extremes previously observed have disappeared. 180 190 200 210 220 230. -
Incremental Learning of Locally OrthogonalSubspaces for Set-based…
mi.eng.cam.ac.uk/reports/svr-ftp/kim_bmvc06.pdf21 Sep 2006: 0 50 100 150 200 250 300 350 4000.25. 0.2. 0.15. ... Fea. ture. Val. ueBatch OSMINC OSM. 50 100 150 200 250 300 350 4000. -
IEEE TRANS. ON SAP, VOL. ?, NO. ??, ????? ...
mi.eng.cam.ac.uk/~mjfg/liu_ASL07.pdf22 Nov 2006: IEEE TRANS. ON SAP, VOL? , NO? ,? 200? 1. Automatic Model Complexity Control Using. ... 200? 7. as the average phone correctness of all possible word sequences {W̃},. -
DYNAMIC RESOLUTION SELECTIONIN ULTRASONIC STRAIN IMAGING J. E.…
mi.eng.cam.ac.uk/reports/svr-ftp/lindop_tr566.pdf29 Sep 2006: 8. 0 100 200 300 400 500 600. 0. 0.2. 0.4. ... ovar. ianc. e. window length = 50250500. (a). 0 100 200 300 400 5000. -
C:/SFWDoc/Academic/Publications/2005/ICCV_HCI_2005/FinalPaper/iccv_hci…
mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_iccv_hci05.pdf21 Sep 2006: The MGO obtained withinthe region of interest will be rescaled to a standard size, which is 200 200 inthe proposed system. -
Discriminative Adaptation for Speaker Verification C. Longworth and…
mi.eng.cam.ac.uk/~mjfg/longworth_INTER06.pdf22 Nov 2006: τ I 50 100 200 500. EER (%) 12.92 12.81 12.83 12.51 12.33. -
Face Recognition from Video using the GenericShape-Illumination…
mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ECCV06.pdf17 Feb 2006: generations 200. 0 100 200 300 400 500 600 700 8001. ... Maximal generationcount of 200 was chosen as a trade-off between accuracy and matching speed. -
paper563_final.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/thayananthan_eccv06.pdf14 Sep 2006: Fig. 2. RVM regression on a toy dataset. The data set consists of 200 samplesfrom three polynomial functions with added Gaussian noise. ... For testing, 200 poses aregenerated by randomly sampling the same region in parameter space and in-troducing -
stenger_imavis06.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/stenger_imavis06.pdf21 Sep 2006: At. 400 200 0 200 4000. 0.01. 0.02. 0.03. 0.04. 0.05. ... a). 100 0 100 200 3000. 0.02. 0.04. 0.06. 0.08. x. -
Learning Discriminative Canonical Correlationsfor Object Recognition…
mi.eng.cam.ac.uk/reports/svr-ftp/kim_eccv06.pdf21 Sep 2006: 9. 100 150 200 250 300 350 4000.5. 0.6. 0.7. 0.8. -
Semi-supervised Learning of Joint DensityModels for Human Pose…
mi.eng.cam.ac.uk/reports/svr-ftp/navaratnam_semi_supervised.pdf14 Sep 2006: The question then is to what extent adding marginal samples. 0 50 100 150 200 250 3002. -
SENSORLESS RECONSTRUCTIONOF UNCONSTRAINED FREEHAND 3D ULTRASOUND DATA …
mi.eng.cam.ac.uk/reports/svr-ftp/housden_tr553.pdf22 May 2006: SENSORLESS RECONSTRUCTIONOF UNCONSTRAINED FREEHAND. 3D ULTRASOUND DATA. R. J. Housden, A. H. Gee,G. M. Treece and R. W. Prager. CUED/F-INFENG/TR 553. May 2006. University of CambridgeDepartment of Engineering. Trumpington StreetCambridge CB2 1PZ. -
TextonBoost: Joint Appearance, Shape andContext Modeling for…
mi.eng.cam.ac.uk/reports/svr-ftp/shotton_eccv06.pdf15 Feb 2006: 9. (a)0 100 200 300 400 500. 0. 2. 4. 6. -
pami04.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/stenger_pami06.pdf21 Sep 2006: 10. 20. 30. 40. Frame. RM. S e. rror. (b). 0 50 100 150 200 250 300 350 400 450 5000. -
1 Model-Based Hand Tracking Using a HierarchicalBayesian Filter…
mi.eng.cam.ac.uk/reports/svr-ftp/thayananthan_pami06.pdf14 Sep 2006: 10. 20. 30. 40. Frame. RM. S e. rror. (b). 0 50 100 150 200 250 300 350 400 450 5000.
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