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  1. Results that match 1 of 2 words

  2. 22 Nov 2006: The various models andrecognition configurations are evaluated using several recent BNdevelopment and evaluation test sets. ... Test set # Shows Hours Period. dev03 6 3 Jan. 2001eval03 6 3 Feb.
  3. 22 Nov 2006: Though gains inthe posterior of the correct speaker were obtained in training thesedid not generalise well to the test data. ... Eurospeech, 1997. [11] A. Martin, “The NIST year 2002 speaker recog-nition evaluation plan,” 2002, Available
  4. 22 Nov 2006: C-Aug ML CML 7.3 9.1. Table 1. Training and test error rates for CAN/CAN’T. ... model (tests on MMI HMMssuggest that this may yield a gain of up to 0.5% absolute).
  5. C:/SFWDoc/Academic/Publications/2005/BMVC_2005/FinalPaper/bmvc_05_sfwo…

    mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_bmvc05.pdf
    21 Sep 2006: cluttered background, and background with skin colour). The overallaccuracyon 1025 test cases is 89.7%. ... Thepercentage of test cases that cannot be mapped into any classis 20.3%.
  6. Face Set Classification using Maximally Probable Mutual Modes Ognjen…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ICPR06.pdf
    29 Apr 2006: To establish baseline performance, we compared ourrecognition algorithm to:. • State-of-the-art commercial system FaceItr by Identix[8] (the best performing software in the recent FaceRecognition Vendor Test [10]),. • ... perform well if imaging
  7. TextonBoost: Joint Appearance, Shape andContext Modeling for…

    mi.eng.cam.ac.uk/reports/svr-ftp/shotton_eccv06.pdf
    15 Feb 2006: e) A test input with textons t1 and t2 in the same relative positionas that of training. ... Quantitative evaluation. Figure 8 shows the confusion matrix obtained byapplying our algorithm to the test image set.
  8. 22 Nov 2006: Only 0.3% improvement wasobtained on this test set. 3See http://htk.eng.cam.ac.uk/docs/cuhtk.shtml4Significance tests were carried out using the NIST Scoring Toolkit. ... These systems wereevaluated on thedev03 andeval03 test sets, each consistingof 3
  9. 5 Jul 2006: Evaluation on held-out data (eval03)– 6 hours of test data– decoded using LVCSR trigram language model– baseline using confusion network decoding. ... φcn(O; λ) =[ F(ω1) F(ω2). φ(O; λ). ]. • Incorporating in score-space requires consistency
  10. 5 Jun 2006: The secondtest set was based on the 1000 word DARPA Resource Management test set. ... 71. 8.1 Average SNR for the RM test sets adding Lynx Helicopter noise attenuatedby 20dB.
  11. stenger_imavis06.dvi

    mi.eng.cam.ac.uk/reports/svr-ftp/stenger_imavis06.pdf
    21 Sep 2006: The parameters for both methods are setby testing the classification performance on a test setof 5000 images. ... In a first approach,the edge and colour cost terms are computed for a numberof test images.
  12. 22 Nov 2006: 3. INCREMENTAL BAYESIAN ADAPTATION. The Bayesian adaptation discussed in section 2 runs in a batchmode where all test data are assumed to be available before adap-tation. ... Theperformance was evaluated on the 2003 evaluation test dataset,eval03,
  13. Sparse and Semi-supervised Visual Mapping with the S3GP Oliver ...

    mi.eng.cam.ac.uk/reports/svr-ftp/williams_cvpr06.pdf
    3 Apr 2006: In [14], error is computed using a“leave-one-out” test rather than with completely new testdata. ... A leave-one-out test for gaze-tracking data with theS3GP gives an error of 0.68.
  14. IEEE TRANS. ON SAP, VOL. ?, NO. ??, ????? ...

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/mjfg_ASL.pdf
    23 Feb 2006: The various models andrecognition configurations are evaluated using several recent BNdevelopment and evaluation test sets. ... Test set # Shows Hours Period. dev03 6 3 Jan. 2001eval03 6 3 Feb.
  15. Face Recognition from Video using the GenericShape-Illumination…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ECCV06.pdf
    17 Feb 2006: In AFR tests, such methods are usuallyoutperformed by methods from the third class: view-based techniques e.g. ... KLD) [38]. In all tests, both training data for each person in the gallery, as well as test data,consisted of only a single sequence.
  16. 22 Nov 2006: This is used both within a cross-validationframework and with a held-out test set, the eval03 dataset [20]. ... This is easilydemonstrated on the 6-hour eval03 test set [20]. SVMswere trained to disambiguate ten of the most confusablepairs.
  17. 22 Nov 2006: Evaluation on held-out data (eval03)– 6 hours of test data– decoded using LVCSR trigram language model– baseline using confusion network decoding. ... φcn(O; λ) =[ F(ω1) F(ω2). φ(O; λ). ]. • Incorporating in score-space requires consistency
  18. 22 Nov 2006: Systems aretrained using the 296 hours switchboard data (h5etrain03 )and evaluated on a 3-hour test set (dev01sub ). All systemsin this paper used 12 PLP coefficients with theC0 term plusthe first, ... 1Significance tests were carried out using the NIST
  19. Multi-Sensory Face Biometric Fusion (for Personal Identification)…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_OTCBVS06.pdf
    19 Mar 2006: This is challenging across large posevariations, such as those contained in our test set. ... Face recognition vendor test 2002. Technical report,National Institute of Standards and Technology, 2003.
  20. johnson06stable.dvi

    mi.eng.cam.ac.uk/reports/svr-ftp/johnson_stable06.pdf
    18 Sep 2006: create a set of such images for their tests in [7]), avideo taken of the object in its environment (e.g. ... The first setting was used as training, with the others used as test sets.
  21. Explicitly Generating Complementary Systems for Large…

    mi.eng.cam.ac.uk/~mjfg/breslin_INTER06.pdf
    22 Nov 2006: Thus, the final fea-ture vector has 42 dimensions. Results are given on two test sets:dev04f consists of 0.5 hours of CCTV data from shows broad-cast in November ... Thiseffect is seen for both complementary models, on both test sets.

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