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  2. ./plot_entropy.eps

    mi.eng.cam.ac.uk/~ar527/chen_is2017.pdf
    15 Jun 2018: Thus linear interpolation is challenging for bi-LMs. 3.2. Log-linear Interpolation. An alternative approach is to apply linear interpolation inthe logdomain, log-linear interpolation [20]. ... 2015. [20] Alexander Gutkin, “Log-linear interpolation of

  3. 0000010020030040050060070080090100110120130140150160170180190200210220…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2017-BMVC-bayesian-SegNet.pdf
    13 Mar 2018: 0 10 20 30 40 50 6079. 79.5. 80. 80.5. 81. ... Pascal VOC12 segmentation challenge [9] consists of segmenting 20 salient objectclasses from widely varying backgrounds.

  4. 0000010020030040050060070080090100110120130140150160170180190200210220…

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2017-BMVC-bayesian-SegNet.pdf
    13 Mar 2018: 0 10 20 30 40 50 6079. 79.5. 80. 80.5. 81. ... Pascal VOC12 segmentation challenge [9] consists of segmenting 20 salient objectclasses from widely varying backgrounds.

  5. 0000010020030040050060070080090100110120130140150160170180190200210220…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2011-3DIMPVT-3D-interestpoints.pdf
    13 Mar 2018: V-FAST Building on the success of FAST corner detec-tor [20], Yu et al. ... 75%. qu. art. ile. s). 0 10 20 30 40 50 60 70 80 900.

  6. 0000010020030040050060070080090100110120130140150160170180190200210220…

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2011-3DIMPVT-3D-interestpoints.pdf
    13 Mar 2018: V-FAST Building on the success of FAST corner detec-tor [20], Yu et al. ... 75%. qu. art. ile. s). 0 10 20 30 40 50 60 70 80 900.

  7. 1 SegNet: A Deep ConvolutionalEncoder-Decoder Architecture for Scene…

    mi.eng.cam.ac.uk/~cipolla/publications/article/2016-PAMI-SegNet.pdf
    13 Mar 2018: This idea was inspired from an archi-tecture designed for unsupervised feature learning [20]. ... 20]. The key learningmodule is an encoder-decoder network. An encoder consists ofconvolution with a filter bank, element-wise tanh non-linearity,max-pooling

  8. 1 SegNet: A Deep ConvolutionalEncoder-Decoder Architecture for Scene…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2016-PAMI-SegNet.pdf
    13 Mar 2018: This idea was inspired from an archi-tecture designed for unsupervised feature learning [20]. ... 20]. The key learningmodule is an encoder-decoder network. An encoder consists ofconvolution with a filter bank, element-wise tanh non-linearity,max-pooling

  9. 1 SegNet: A Deep ConvolutionalEncoder-Decoder Architecture for Scene…

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/article/2016-PAMI-SegNet.pdf
    13 Mar 2018: This idea was inspired from an archi-tecture designed for unsupervised feature learning [20]. ... 20]. The key learningmodule is an encoder-decoder network. An encoder consists ofconvolution with a filter bank, element-wise tanh non-linearity,max-pooling

  10. 1 SegNet: A Deep ConvolutionalEncoder-Decoder Architecture for Scene…

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2016-PAMI-SegNet.pdf
    13 Mar 2018: This idea was inspired from an archi-tecture designed for unsupervised feature learning [20]. ... 20]. The key learningmodule is an encoder-decoder network. An encoder consists ofconvolution with a filter bank, element-wise tanh non-linearity,max-pooling

  11. 1 Semi-Supervised Video Segmentation usingTree Structured Graphical…

    mi.eng.cam.ac.uk/~cipolla/publications/article/2013-PAMI-video-segmentation.pdf
    13 Mar 2018: segmentation. 2.1 Unsupervised Video SegmentationThe rectangular patch-based Epitome model [18], [19] andthe pixel based Jigsaw model [20] learn a compact latentrepresentation of an image or sequence of images.

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