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stenger_imavis06.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/stenger_imavis06.pdf21 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. -
Sparse and Semi-supervised Visual Mapping with the S3GP Oliver ...
mi.eng.cam.ac.uk/reports/svr-ftp/williams_cvpr06.pdf3 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. -
Journal of VLSI Signal Processing manuscript No.(will be inserted ...
mi.eng.cam.ac.uk/~mjfg/layton_JVLSI07.pdf22 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. -
Face Recognition from Video using the GenericShape-Illumination…
mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ECCV06.pdf17 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. -
Temporally Varying Model Parameters forLarge Vocabulary Continuous…
mi.eng.cam.ac.uk/~mjfg/sim_INTER05.pdf22 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 -
Explicitly Generating Complementary Systems for Large…
mi.eng.cam.ac.uk/~mjfg/breslin_INTER06.pdf22 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. -
Multi-Sensory Face Biometric Fusion (for Personal Identification)…
mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_OTCBVS06.pdf19 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. -
paper.dvi
mi.eng.cam.ac.uk/~mjfg/liao_INTER06.pdf22 Nov 2006: Table 1: Clean, matched andSPLICE on AURORA 2.0 test set A,averaged across N1-N4, WER(%). ... M-Joint1 2.43 3.82 6.97 17.1416 1.95 2.80 4.23 9.89. Table 2: Model-basedJoint systems’ performance on AURORA2.0 test set A, averaged -
johnson06stable.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/johnson_stable06.pdf18 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. -
Joint Uncertainty Decoding for Noise Robust Speech Recognition H. ...
mi.eng.cam.ac.uk/~mjfg/liao_INTER05.pdf19 Dec 2006: When models trainedin clean conditions are used in the real world, the mismatchbetween the training conditions and the test causes significantloss in recognition accuracy. ... Here. P (šn|xt, M̌) P (šn|yt, M̌) (10). where the model M̌ is now
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