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  2. The terrific TV camera

    mi.eng.cam.ac.uk/IALego/TV.html
    1 Jan 2024: The middle support can be flicked backwards and forwards to accommodate different length lasers. ... this test card and scan it with your camera. Do the squares remain square at all positions in the image?
  3. MORTGAGE DEFAULT: CLASSIFICATION TREES ANALYSIS David Feldman* and…

    mi.eng.cam.ac.uk/~mjfg/local/4F10/Feldman_Gross.pdf
    15 Nov 2005: Cross-Validation method, and the Test-Sample method. In the former, the learning. ... replace the more costly Cross-Validation misclassification estimation by the. Test-Sample method.
  4. 20 Feb 2018: Contrasts marked are statisticallysignificant (p < 0.05) using a Kruskal-Wallis rank sum test. ... Test System Num Objective Success Rate Perceived Average WERDialogs Partial Full Success Rate Turns.
  5. DESIGN OF FAST LVCSR SYSTEMS G. Evermann & P.C. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/evermann_asru2003.pdf
    23 Sep 2003: For BN the test datais taken from radio and TV news shows (for example CNNHeadline News, ABC World News Tonight). ... The 2003 BNeval test set consists of 6 half-hour excerpts from Radio andTV broadcasts taken from February 2001.
  6. paper.dvi

    mi.eng.cam.ac.uk/~mjfg/wang_icassp13.pdf
    13 Jun 2013: Part of theretransmitted data was held-out to form a test set, dev1. ... Foreach of the channels there was 2 to 2.5 hours test data, de-pending on how much of the retransmitting speech passedquality assurance tests.
  7. Robust Instance Recognition in Presence ofOcclusion and Clutter Ujwal …

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2014-ECCV-3D-recognition.pdf
    13 Mar 2018: We capture six test scenes with the same five objects. Eachtest scene has 400 500 frames containing multiple objects with different back-grounds/clutter and poses.Scenario 4: This scenario tests ... Recall. Pre. cis. ion. LineModSupp. SIterative(Edge).
  8. Ghostscript wrapper for…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2007-CVPR-Kim-incremental.pdf
    13 Mar 2018: test data. The descriptor should also be compact, even for. large data sets. ... divided into training and test sets. All basis vectors were. extracted from the training set.
  9. Segment Generation and Clustering in the HTKBroadcast News…

    mi.eng.cam.ac.uk/reports/svr-ftp/hain_darpa98.pdf
    8 Mar 2000: The test set is split into shows available bothin training and test and test only. ... Taking advantage of this effect, all segmentsare then split up again in the middle of silence segments clustering isrepeated.
  10. 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.
  11. 12 Apr 2022: You are required to design, implement, test and evaluate a program writtenin C++ to display and analyse the past trading price data. ... Session 4 Shipping working functions to team directory(Day 2 afternoon) Testing on test data sets 60 minutes.
  12. Efficient Large-Scale Semantic VisualLocalization in 2D Maps Tomas…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2020-ACCV-Large-scale-localization.pdf
    28 Jun 2021: database of embeddings of the test environmentlocations to retrieve the most similar location. ... The plots in the middle show mean confidence of trajectories w.r.t.
  13. Contour-Based Learning for Object Detection Jamie ShottonDepartment…

    mi.eng.cam.ac.uk/reports/svr-ftp/shotton_iccv05.pdf
    8 Aug 2005: Test-ing was performed on 164 images containing 193 cars,and164 background images. ... Our technique relies on edge features andhigher-resolution training and test images would certainlyimprove results.
  14. 20 Feb 2018: The environment T in a training dia-logue might be different from that of the test dialogues, and thuswe computed a maximum-entropy randomised policy in the testenvironments given the learnt ... In future work, theIRL reward function will be integrated
  15. 20 Feb 2018: Table 3Percent of unseen contexts in the test data. Number of matching features. ... Noduration modification was applied for this test. Twenty subjects participated in the evaluation.
  16. paper.dvi

    mi.eng.cam.ac.uk/reports/svr-ftp/kim_icslp04.pdf
    10 Jan 2005: The transcription is either known in training orobtained by an initial, non-VTLN, decoding pass for test data.If and are the original and transformed feature vectorsrespectively then the log-likelihood ... The systems were eval-uated on two 3 hour test
  17. Optimisation of Fast LVCSR Systems Gunnar Evermann, Phil Woodland ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/evermann_stthomas03.pdf
    10 Dec 2003: P1 speed-accuracy trade-off (CTS eval02). • In eval chose middle operating point for safety Should have used fast setup and use time elsewhere. ... test on eval03: skip 66% segments, 43% audio, 32% rescoring runtimei.e.
  18. IMPLEMENTATION OF AUTOMATIC CAPITALISATIONGENERATION SYSTEMS FOR…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/kim_icassp02.pdf
    9 Aug 2005: We also used 3 hours of test data from the NIST 1998 Hub-4BN benchmark tests. ... Most of these words are not capitalised,if they are used in the middle of sentences.
  19. Towards Automatic Assessment of Spontaneous Spoken English Y.…

    mi.eng.cam.ac.uk/~mjfg/ALTA/publications/ALTA_SpComm2017.pdf
    12 Sep 2018: computed over all the test sectionswhere the candidate is required to produce spontaneousspeech. ... xN}, what is the best estimate of thevalue of the function at test point x.
  20. Ghostscript wrapper for…

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2007-CVPR-Kim-incremental.pdf
    13 Mar 2018: test data. The descriptor should also be compact, even for. large data sets. ... divided into training and test sets. All basis vectors were. extracted from the training set.
  21. Pronunciation modeling by sharing Gaussians

    mi.eng.cam.ac.uk/reports/svr-ftp/nock_csl00.pdf
    31 Jul 2000: Pronunciation modeling by sharing Gaussians 141. TABLE I. WER degradation with speaking style on theMULTI-REG test set. ... Steps (6), (3), (4) and (5) arethen carried out in that order to estimate and test a matched pronunciation model.

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