Sentence examples for signature representations from inspiring English sources

Exact(1)

Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision.

Similar(59)

Additionally, the user decides the level of molecular resolution to use in the molecular signature representation.

Likewise, reaction signatures, which are biochemical reactions coded into the molecular signature representation (Equation 7 in Methods), are used in order to search for and enumerate similar reactions.

We have shown in a previous study [ 46] that enzyme multispecificity and promiscuity are properties that can be characterized by using a molecular signature representation.

Using the optimal SVT approach above, three image signatures (representations) can be derived: (i) signature (1st) based on histogram of dense-patch SIFT descriptors; (ii) signature (2nd) based on kernel density of dense-patch SIFT descriptors; and (iii) signature (3rd) based on histogram of dense-patch DAISY descriptors.

Based on dense patch DAISY and dense patch SIFT, we have two sets of image signatures (representations): (left { mathbf {F}_{q},left { mathbf {F}_{d_{m}}right }_{m=1}^{M}right } ) and (left { mathbf {G}_{q},left { mathbf {G}_{d_{m}}right }_{m=1}^{M}right } ), respectively.

Collier moved to England at the very end of the 17th century, and thereafter started to paint what became his signature works: illusionistic representations of letter racks, in which painted letters, combs, sealing wax and dog-eared political pamphlets are tucked in behind painted strips of leather.

Consequently, examination of the proportion of GO annotations in the one-hop neighborhood of this signature identified over-representations of terms related to cell proliferation and death, while the direct interactors only showed over-representation of terms associated with the immune system (Figure S1B).

Using this, we define the signature of tempered genuine representations of Mp(n,R).

To address both the difficulty of obtaining good features, as well as improve system performance, we propose learning the representations from signature images, in a Writer-Independent format, using Convolutional Neural Networks.

The classification performance of our signature is evident in representations that indicate as first approximation the up-regulation of the signature in hypoxic condition.

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