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Convolutional Neural Network
Convolutional Neural Network

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!!! Overview
[{$pagename}] ([CNN]) is a class of deep, [feedforward Neural network] that has successfully been applied to analyzing visual imagery.
[{$pagename}] use a variation of multilayer [perceptrons] designed to require minimal preprocessing.
[{$pagename}] are also known as shift invariant or [Space Invariant Artificial Neural Network]s ([SIANN]), based on their shared-weights architecture and translation invariance characteristics.
[{$pagename}]s were inspired by biological processes in which the connectivity pattern between [neurons] is inspired by the organization of the animal visual cortex. Individual cortical [neurons] respond to stimuli only in a restricted region of the visual field known as the receptive field. The receptive fields of different [neurons] partially overlap such that they cover the entire visual field.
[{$pagename}]s use relatively little pre-processing compared to other image classification algorithms. This means that the [{$pagename}] learns the filters that in traditional algorithms were hand-engineered. This independence from prior knowledge and human effort in feature design is a major advantage.
They have applications in image and video [recognition], recommender systems and natural language processing.
[{$pagename}] has many drivitives:
* multi-delay sync (MDS) network - to align and predict [emotion] annotations
!! Category
%%category [Artificial Intelligence]%%
!! More Information
There might be more information for this subject on one of the following:
[{ReferringPagesPlugin before='*' after='\n' }]
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* [#1] - [Convolutional_neural_network|Wikipedia:Convolutional_neural_network|target='_blank'] - based on information obtained 2017-11-24-
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop