Topic
Representation (systemics)
About: Representation (systemics) is a research topic. Over the lifetime, 33821 publications have been published within this topic receiving 475461 citations.
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TL;DR: In this paper, critical discourse analysis of over 450 media texts produced between 2009 and 2017, the authors reported the conceptual understanding of digital-free tourism, the ways the media representation has changed over time and explored the broad social context and debates in which the concept is embedded.
86 citations
Proceedings Article•
01 Jun 1993
85 citations
Patent•
29 Sep 1998
TL;DR: In this article, a connection tree is formed from the parent graphical object which has the initial values of each property of the child graphical objects, and the altered value is broadcast through the connection tree to allow recalculation of each child object's property based upon its initial value so that the parent object and its child objects can be graphically displayed based on the changed position.
Abstract: A graphical object in an object-oriented environment is comprised of a plurality of child graphical objects. The parent graphical object and each of the child graphical objects have a property corresponding to the orientation of a representation of the respective object. A connection tree is formed from the parent graphical object which has the initial values of each property of the child graphical objects. During operation, the value of the property of the graphical object may be altered corresponding to a change in the position of the object's graphical representation. The altered value is broadcast through the connection tree to allow recalculation of each child object's property based upon its initial value so that the parent object and its child objects can be graphically displayed based on the changed position.
85 citations
Patent•
15 Dec 2003
TL;DR: In this article, a method and an apparatus automatically recognize or verify objects in a digital image using probability models, by accessing digital image data including an object of interest therein, detecting an object in the image, normalizing the object to generate a normalized object representation, extracting a plurality of features from the normalized object representations, and applying each feature to a previously-determined additive probability model to determine the likelihood that the objects of interest belongs to an existing class.
Abstract: A method and an apparatus automatically recognize or verify objects in a digital image using probability models. According to a first aspect, a method and apparatus automatically recognize or verify objects in a digital image by: accessing digital image data including an object of interest therein; detecting an object of interest in the image; normalizing the object to generate a normalized object representation; extracting a plurality of features from the normalized object representation; and applying each feature to a previously-determined additive probability model to determine the likelihood that the object of interest belongs to an existing class. In one embodiment, the previously-determined additive probability model is an Additive Gaussian Model.
85 citations
85 citations