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  1. Results that match 1 of 2 words

  2. MVA'94 IAPR Workshop on Machine Vision Applications Dec. 13-15,…

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/1994-MVA-pointing.pdf
    13 Mar 2018: Performance. By observing feedback from the robot, the op- erator is able to position the gripper to within lcm: sufficient accuracy to instruct it to pick up n small wootlcn Ilock
  3. A Simple Technique for Self-Calibration

    mi.eng.cam.ac.uk/reports/svr-ftp/mendonca_self-calibration.pdf
    10 Aug 1999: This goal is achieved by solving an op-timization problem by numerical techniques, searching di-rectly for the intrinsic parameters of the cameras, instead ofthe indirect search performed by the algorithms
  4. 20 Feb 2018: Note that the reward model and the dialogue policy are being jointly op-timised during the sequence of dialogues.
  5. main.dvi

    mi.eng.cam.ac.uk/~sjy/papers/ywss05.pdf
    20 Feb 2018: ruleset = ruledef";" { ruledef ";" } {dbasefile}ruledef = lassdef | lexdef lassdef = lassinst "->" [sub lass [ lassbody [ ond [prob lassbody = "(" [opt member { "," [opt member } ")"lexdef = lassinst "=" "(" atom[prob {"|" atom[prob ")"prob = "{"
  6. 13 Mar 2018: "!# $%& %'()#,&-##)./10324 56&-786&9: ;#<: =;#: >?@-<;A66"B9: ;#<: =;#: >? C<DFEGHIJBGKMLONQPLSRLTU(VQLP LXWZYQ[&R]ARR[&T_T_UVALO]QRLOBaNFLPSL=NQU ]bWBcdP ]QNA[eTAdfUf[&ghNQPBiLRU P]QSU]QP LjWBTQYhLdghU[&ThPLBiLP kXWlc&dP
  7. 9 Aug 2005: "!# $%& %'()#,&-##)./10324 56&-786&9: ;#<: =;#: >?@-<;A66"B9: ;#<: =;#: >? C<DFEGHIJBGKMLONQPLSRLTU(VQLP LXWZYQ[&R]ARR[&T_T_UVALO]QRLOBaNFLPSL=NQU ]bWBcdP ]QNA[eTAdfUf[&ghNQPBiLRU P]QSU]QP LjWBTQYhLdghU[&ThPLBiLP kXWlc&dP
  8. Multi-Sensory Face Biometric Fusion (for Personal Identification)…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_OTCBVS06.pdf
    19 Mar 2006: The optimal. values were found to be2.3 and6.2 for visual data; the op-timal filter for thermal data was found to be alow-passfilterwith W2 = 2.8 (i.e.
  9. A NEURAL NETWORK BASED, SPEAKER INDEPENDENT, LARGE…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/wernicke_eurospeech93.pdf
    9 Aug 2005: 1.3. ComputingThe HMM-ANN approach is very computationally expensive.The networks currently require about 1013 floating point op-erations to train and future estimates of the required computepower is one
  10. 22 Nov 2006: Theseallow high-dimensional kernel feature-spaces to be de-fined and calculated using only simple transducer op-erations on discrete sequences (or lattices) of observa-tions.
  11. PoseNet: A Convolutional Network for Real-Time 6-DOF Camera…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2015-ICCV-relocalisation.pdf
    13 Mar 2018: engineering or graph op-timisation. ... This demonstrates that learning with the op-timum scale factor leads to the convnet uncovering a more accuratepose function.

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