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Scientific visualization (also spelled scientific visualisation) is an interdisciplinary branch of science concerned with the visualization of scientific phenomena. [2] It is also considered a subset of computer graphics, a branch of computer science. The purpose of scientific visualization is to graphically illustrate scientific data to enable ...
Computational geometry applies computer algorithms to representations of geometrical objects. Theoretical computer science includes areas of discrete mathematics relevant to computing. It draws heavily on graph theory and mathematical logic. Included within theoretical computer science is the study of algorithms and data structures.
[24] [25] P. Guha et al. Statlog (Image Segmentation) Dataset The instances were drawn randomly from a database of 7 outdoor images and hand-segmented to create a classification for every pixel. Many features calculated. 2310 Text Classification 1990 [26] University of Massachusetts: Caltech 101: Pictures of objects. Detailed object outlines ...
This is a list of graphical methods with a mathematical basis. Included are diagram techniques, chart techniques, plot techniques, and other forms of visualization . There is also a list of computer graphics and descriptive geometry topics .
An object graph is a view of an object system at a particular point in time. Unlike a normal data model such as a Unified Modeling Language (UML) class diagram, which details the relationships between classes, the object graph relates their instances. Object diagrams are subsets of the overall object graph.
Graphic representation of a minute fraction of the WWW, demonstrating hyperlinks.. Graph drawing is an area of mathematics and computer science combining methods from geometric graph theory and information visualization to derive two-dimensional depictions of graphs arising from applications such as social network analysis, cartography, linguistics, and bioinformatics.
For example, if the objects are long and thin, then a sphere will enclose mainly empty space compared to a box. Boxes are also easier to generate hierarchical bounding volumes. Note that using a hierarchical system like this (assuming it is done carefully) changes the intersection computational time from a linear dependence on the number of ...
Used to teach, explain and/or simply concepts. For example, organisation charts and decision trees. idea generation (conceptual & exploratory). [64] Used to discover, innovate and solve problems. For example, a whiteboard after a brainstorming session. visual discovery (data-driven & exploratory). [64] Used to spot trends and make sense of data.