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  2. Template matching - Wikipedia

    en.wikipedia.org/wiki/Template_matching

    Template matching [1] is a technique in digital image processing for finding small parts of an image which match a template image. It can be used for quality control in manufacturing, [ 2 ] navigation of mobile robots , [ 3 ] or edge detection in images.

  3. Sample entropy - Wikipedia

    en.wikipedia.org/wiki/Sample_entropy

    Like approximate entropy (ApEn), Sample entropy (SampEn) is a measure of complexity. [1] But it does not include self-similar patterns as ApEn does. For a given embedding dimension, tolerance and number of data points, SampEn is the negative natural logarithm of the probability that if two sets of simultaneous data points of length have distance < then two sets of simultaneous data points of ...

  4. Template modeling score - Wikipedia

    en.wikipedia.org/wiki/Template_modeling_score

    The TM-score indicates the similarity between two structures by a score between (,], where 1 indicates a perfect match between two structures (thus the higher the better). [1] Generally scores below 0.20 corresponds to randomly chosen unrelated proteins whereas structures with a score higher than 0.5 assume roughly the same fold. [ 2 ]

  5. Matching pursuit - Wikipedia

    en.wikipedia.org/wiki/Matching_pursuit

    Matching pursuit should represent the signal by just a few atoms, such as the three at the centers of the clearly visible ellipses. Matching pursuit (MP) is a sparse approximation algorithm which finds the "best matching" projections of multidimensional data onto the span of an over-complete (i.e., redundant) dictionary .

  6. Multiple-scale analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple-scale_analysis

    Higher-order solutions – using the method of multiple scales – require the introduction of additional slow scales, i.e., t 2 = ε 2 t, t 3 = ε 3 t, etc. However, this introduces possible ambiguities in the perturbation series solution, which require a careful treatment (see Kevorkian & Cole 1996; Bender & Orszag 1999). [2]

  7. Multiclass classification - Wikipedia

    en.wikipedia.org/wiki/Multiclass_classification

    Firstly, the scale of the confidence values may differ between the binary classifiers. Second, even if the class distribution is balanced in the training set, the binary classification learners see unbalanced distributions because typically the set of negatives they see is much larger than the set of positives.

  8. Mako (template engine) - Wikipedia

    en.wikipedia.org/wiki/Mako_(template_engine)

    Mako is a template library written in Python. Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance. The Mako template is used by Reddit. [4] It is the default template language included with the Pylons [5] and Pyramid [6] web frameworks.

  9. Jinja (template engine) - Wikipedia

    en.wikipedia.org/wiki/Jinja_(template_engine)

    Jinja is a web template engine for the Python programming language. It was created by Armin Ronacher and is licensed under a BSD License. Jinja is similar to the Django template engine, but provides Python-like expressions while ensuring that the templates are evaluated in a sandbox. It is a text-based template language and thus can be used to ...