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This theory of recognition is based on a more holistic system rather than by parts, suggesting that objects are stored in memory with multiple viewpoints and angles. This form of recognition requires a lot of memory as each viewpoint must be stored. Accuracy of recognition also depends on how familiar the observed viewpoint of the object is. [14]
Pandemonium architecture is a theory in cognitive science that describes how visual images are processed by the brain. It has applications in artificial intelligence and pattern recognition. The theory was developed by the artificial intelligence pioneer Oliver Selfridge in 1959. It describes the process of object recognition as the exchange of ...
Memory modules. There are two kinds of memory modules in ACT-R: Declarative memory, consisting of facts such as Washington, D.C. is the capital of United States, France is a country in Europe, or 2+3=5; Procedural memory, made of productions. Productions represent knowledge about how we do things: for instance, knowledge about how to type the ...
Template matching theory describes the most basic approach to human pattern recognition. It is a theory that assumes every perceived object is stored as a "template" into long-term memory. [4] Incoming information is compared to these templates to find an exact match. [5]
Memory segmentation; Locality of reference; Logical disk; Storage virtualization; Virtual memory; Memory-mapped file; Software entropy; Software rot; In-memory database; In-memory processing; Persistence (computer science) Persistent data structure; RAID; Non-RAID drive architectures; Memory paging; Bank switching; Grid computing; Cloud ...
Memory architecture describes the methods used to implement electronic computer data storage in a manner that is a combination of the fastest, most reliable, most durable, and least expensive way to store and retrieve information. Depending on the specific application, a compromise of one of these requirements may be necessary in order to ...
An optical neural network is a physical implementation of an artificial neural network with optical components. Early optical neural networks used a photorefractive Volume hologram to interconnect arrays of input neurons to arrays of output with synaptic weights in proportion to the multiplexed hologram's strength. [ 2 ]
In 1974, Baddeley and Hitch [5] introduced and made popular the multicomponent model of working memory.This theory proposes a central executive that, among other things, is responsible for directing attention to relevant information, suppressing irrelevant information and inappropriate actions, and for coordinating cognitive processes when more than one task must be done at the same time.