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The image and motion features of patches extracted from each key-frame are collected and used to train an appearance motion codebook.
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In MOP-CNN [40], CNN features of patch sizes 128 and 64 are used to obtain the VLAD descriptor.
When descriptors of three different patch sizes are combined, such combination is imperfect because the features of patch size 256 were not processed through VLAD.
Moreover, the CNN features of patch size 256 are directly concatenated with the VLAD descriptors generated from patch sizes 64 and 128.
We extract the feature of patches in (G_{y_{l}}^{j}) with the feature extraction operator F in order to boost the prediction accuracy.
This study used standardized, novel patches of habitat as surrogates of natural boulders in order to control the physical features of these patches.
The CRF model is learned based on sparse features of local patches in a multi-scale structure and it also takes the contextual information of target into consideration.
To find the best subdictionary among the collection of learned subdictionaries for each noisy patch, we compare representative features of the patch (y i ) and each subdictionary.
They are now the dominant features of the patch.
Several features of the patch-reef array at Glover's Atoll make this reserve an ideal model system to test the applicability of landscape ecology approach to marine reserve evaluation.
Use (mathbf {D}_{h}in mathbb {R}^{ntimes K}) and (mathbf {D}_{l}in mathbb {R}^{mtimes K}) to denote the over-complete dictionaries of K atoms (K>n,K>m), which are trained from HR and the feature of LR patches from training images, respectively.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com