Cognitive Vision Systems (CVSys) are systems that combine computer vision with reasoning and semantic interpretation components to achieve high-level tasks.
For interpretation, principal components were rotated using the varimax rotation method, an orthogonal rotation procedure.
An important characteristic of linear dimensionality reduction methods such as PCA is the intuitive interpretation of components in the low-dimensional space in terms of the original dimensions.
Inspection of a scree plot of unrotated components was used to determine the number of factors, followed by varimax rotation of the final solution to assist in the interpretation of components.
According to this interpretation, these components should have been elicited contralateral to the cued movement goal location on the left or right side, but that was not what was observed.
The method is described in four steps: the accuracy of image acquisition, representation of the object outline, calculation of components and interpretation of the components, all focusing on colloidal food system applications.
The questionnaire proposed several interpretations of components of the Swiss cheese model: a) slice of cheese, b) hole, c) arrow, d) active error, e) how to make the system safer.
A grammar, in Lewis's sense, is a lexicon (i.e. a set of elementary constituents, along with their interpretation), a generative component (i.e. rules for combining constituents into larger constituents), and a representing component (i.e. rules for verbally expressing constituents).
However, we have to be cautious with the interpretation of these component maps because of the way that STEM data is recorded.
Moreover the efficacy of the data interpretation tool principal component analysis (PCA) is debated for potential applications in polymer characterisation and polymer degradation.
